Caring for Capital: How Care Robots Promise to Fix What Austerity Broke

Caring for Capital

How Care Robots Promise to Fix What Austerity Broke

By Nora Weinberger, Dana Mahr, Jérémy Lefint, Bettina-Johanna Krings

Volume 27, no. 3, Public Health

Artwork by Alice Mao

Introduction

Care is in crisis, and the answer, we are told, is a robot. From Tokyo to Berlin to Boston, governments and industry pitch robotic seals, lifting exoskeletons, and AI companions—care robots of various kinds—as answers to a care crisis that, in their telling, is too vast and too rooted in demographic change to be solved any other way.1 The pitch is seductive: Technology will fill the gaps that policy cannot. It is also a misdirection. Behind the brochures lies a simpler story, one of decades of underinvestment in care itself, marketization, and political neglect, and a question the brochures will not ask: Why is care in crisis to begin with?

But demography is not destiny. Far more than simply the result of people living longer, the current strain on long-term care systems is the outcome of decades of political decisions that have treated care as a cost to be contained rather than a public good to be strengthened.2 Chronic underfunding, competitive tendering, and efficiency targets have narrowed staffing levels, intensified work, and degraded working conditions.3 When care workers leave due to low pay and high stress, the resulting shortages are presented as natural scarcity rather than the predictable outcome of what critics call “policy failures in health and education.”4

It is precisely this naturalization of the crisis that opens the door for technological promises. Care robotics is touted as a pragmatic solution. Governments fund pilot projects and innovation programs (e.g., the “Health” cluster of Horizon Europe), while structural reforms around wages, staffing ratios, and public financing remain limited.5 Yet the framing of robotics as a fix deserves scrutiny. We do not argue against technology as such. Rather, we question a political trajectory in which technical innovation substitutes for social reform. More than two decades of fieldwork in care settings, including documenting the voices of care workers themselves, has shown us what that trajectory looks like in practice: Investments flow into devices that monitor, lift, or remind, while the relational, time-intensive, and context-dependent dimensions of care remain under-resourced. This division of resources is also a division of visibility: The parts of care that can be timed, counted, and replicated attract investment, while the slower, attentive, often invisible labor that holds care together is treated as residual.

The central issue is therefore not whether robots can perform certain functions, but why technological fixes are prioritized over rebuilding care as a collectively financed and democratically governed public infrastructure. In what follows, we build this argument from a policy and funding analysis as well as from our own fieldwork in long-term care settings, where care workers, among others, tell a remarkably consistent story.

I: Manufacturing Scarcity

The care crisis is not a natural outcome of demographic change. It is the predictable result of political decisions that have subordinated care work to market logic, and, in doing so, systematically underfunded the public organization of care and shifted responsibility onto families.6 To understand this crisis, a historical perspective is instructive. The 1990s marked a break in socially organized care in almost all European countries. Until 1990, the care of elderly and disabled people was the responsibility of the family and was primarily undertaken by female relatives. With the exception of the Nordic countries, where care policy was already introduced in the early 1960s, no independent policy area existed in Europe with regard to care.

Against this background of converging pressures—women entering paid employment in growing numbers, family structures becoming smaller and more mobile, populations aging—the unpaid familial care arrangement quietly assumed by European welfare states was becoming untenable. Reform debates over financing models and the boundaries of family responsibility were already underway by the mid-2000s.7 They remain unresolved, and the working conditions of care staff have stayed on the policy agenda for years.9 Germany illustrates how this was built into policy from the start. In 1995/96 long-term care was introduced as the fifth pillar of social security. However, this instrument was implemented according to the partial-coverage principle, in which insurance pays only a fixed budget per case rather than the full cost of needed care.10 Thus, the care sector has been transformed into a care market, where individual care activities became commodities. To keep costs down, policymakers have again consciously externalized the burden of insufficient provision onto families. Today, 86 percent of people requiring care are looked after at home, the majority by relatives and most often by women.11 And the trajectory is only continuing: The Federal Statistical Office of Germany estimates already in 2035 6.3 million (+27 percent in contrast to 2021) and in 2055 nearly 7.6 million (+53 percent) people will be in need of care, figures to which there is currently no political response.12

As a result, the structural conditions of care work have only become more entrenched. A 2023 German labor research report names them bluntly: A “decades-long history of low paid work, low social recognition, low levels of collective organization, and a heavy reliance on workers’ professional and personal sense of responsibility” has led to a tremendous decrease in the attractiveness of this profession.13 However, the Federal Institute for Vocational Education and Training in Germany estimates that there will be an additional need for up to 270,000 nursing and healthcare staff by 2035.14 Demand is rising sharply, but the policy response continues to combine increased demand with suppressed wages, frozen staffing ratios, and a financing system designed to contain public expenditure rather than meet social needs. The result is a profession that policy expects to grow without offering the institutional framework to do so.

Before robotics enters that gap, another set of workers already sustain it. Long-term care in high-income countries is held together by transnational care chains: women from Poland, Romania, and Ukraine working as “live-in” carers in private households, often under informal or precarious arrangements, and higher-skilled migrants recruited from the Philippines, India, and Vietnam to staff hospitals and nursing homes whose own systems are then drained of care workers in turn.15 The arrangement is profoundly gendered and profoundly classed, and it works only as long as what these women actually do remains invisible and devalued behind the marketing of “live-in-companions.”16 It is into this already-managed gap that robotics is introduced as a solution.

II: Follow the Money

Funding structures tell a clear story: Care robotics is primarily an innovation project, not a care reform. Across Europe, North America, and East Asia, substantial public resources flow into research, pilot deployments, and market development. While these investments are routinely justified by demographic pressures, they operate within industrial policy frameworks that prioritize technological competitiveness over social infrastructure.

Within the European Union, programs such as Horizon Europe and the Active and Assisted Living Programme have funded numerous projects on robotic assistance and digital care infrastructures. The funding logic is industrial: Deliverables are measured in patents, prototypes, and market readiness, not in caregiver retention or patient wellbeing. National governments complement these efforts with pilot projects in hospitals and nursing homes, framed as responses to workforce shortages yet designed primarily to accelerate innovation cycles.17 The pattern repeats internationally. Japan’s Robot Strategy positions care robotics as a pillar of economic growth and global technological leadership.18 In the United States, the National Robotics Initiative channels federal funding toward commercialization across healthcare sectors.

Private capital follows public investment. Venture funds and technology firms increasingly treat care robotics as an emerging market. Pilot projects in care facilities function as testbeds for future products, while university-industry partnerships translate publicly funded research into commercial applications.19 Through these interactions, a dense scientific-industrial complex of research institutions, firms, and policy actors has emerged. What it stabilizes and expands, in other words, is itself: more research grants, more pilot projects, more market analyses, more policy briefs, regardless of whether the technologies demonstrably improve care.

While public funds flow into robotic prototypes, the migrant care workforce that already absorbs the labor gap receives little of the same attention. There is no gap waiting to be closed by a robot. There is a workforce being kept cheap by being kept socially and politically invisible. The same global economy that produces this labor also produces the robots pitched as its replacement: rare minerals, electronics manufacturing, and supply chains that bind care robotics to the same uneven geography in which migrant care workers are recruited. This is not a coincidence but the standard arithmetic of automation in service industries: Technology rarely replaces workers outright; it fragments their work into measurable components, automates the most expensive, and devalues what remains by reframing it as “support” rather than skilled labor.20

The distribution of funding thus reveals political priorities. Technological development attracts coordinated public and private investment, because it aligns with existing market logics. Structural reforms advance far more slowly: Improved wages, higher staffing ratios, and sustainable public financing are recognizable as redistributive choices that directly oppose entrenched institutional and class interests. Care robotics moves faster. It is framed as technical rather than political, as pragmatic rather than ideological, and so it sidesteps the conflicts that structural reform cannot avoid. But care robotics is not engineering in any neutral sense. It is the outcome of deliberate choices about where resources should go. Hospital launches pair claims of enabling caregivers with marketing imagery of robots treating patients without them. The signal value of the technology runs on a different logic than the everyday work it is supposed to support.

III: What Robots Cannot Do

Technological development is not neutral but follows a specific rationality of standardization, scalability, and efficiency. Systems are designed to function reproducibly, be transferable across contexts, and remain economically viable. In a care system shaped by austerity and chronic underfunding, this logic gains traction. It is in this context that care robots and exoskeletons do not emerge by chance but as technological responses to politically produced crises, promising efficiency, cost-effectiveness, and predictability.21

Yet this promise rests on a fundamental mismatch. Technical systems excel at clearly defined and measurable tasks. Care, however, is relational. What does that mean in practice? Consider a nurse trying to give medication to a person with dementia who refuses it. There is no protocol that solves this. The nurse must read the moment—body language, tone, what worked yesterday and what didn’t, who else is in the room—and decide whether to try again now, wait, or sit with the refusal until it passes.22 The decision is temporal, context-sensitive, and built on tacit knowledge that has accumulated over years of working with this particular person. None of it can be standardized or scaled without transforming care.23

What a system can actually “do” is not determined in the lab but in everyday practice, within concrete situations, shaped by social expectations and ongoing adjustments.24 Empirical research shows that robotic care technologies do not merely support care but actively reshape it.25 They shift attention toward measurable and controllable aspects, such as vital signs, mobility, and medication schedules, while relational dimensions recede. Rather than technology adapting to care, care becomes aligned with technological logic.26

An illustrative example is the widespread loneliness among care recipients, itself a result of structural social neglect, which is now used to legitimize the deployment of companion robots. These systems reduce missing human relationships to technical functions by simulating responsiveness through scripted and increasingly AI-based interactions. They soothe or occupy rather than genuinely engage. From simple therapeutic devices to advanced AI companions, such systems exemplify how care is reframed as a set of simulatable interaction patterns, where relationships are no longer lived but modeled.

The same mismatch reappears at a different scale. When monitoring systems flag risks, algorithms suggest interventions, and automated decisions shape daily routines, responsibility becomes diffuse—distributed across devices, software, and staff. Yet when something goes wrong, the diffusion stops. Care workers face the disciplinary procedures, the legal liability, and the moral distress of being held responsible for outcomes they did not control.27 Behind these specific tensions sits a more fundamental question. The criteria of “good care” are not identical to those of technological development. The key question, therefore, is not how care can be technically optimized, but whether care should be evaluated according to the logics of efficiency, standardization, and scalability through which technological systems are designed. Those who provide care have their own answers.

IV: Voices from the Floor

Care workers experience firsthand what technology can and cannot deliver, and their accounts reveal a sharp tension between the promises of innovation and everyday practice.

This tension begins with skepticism. Many care workers doubt that automated systems can grasp what care requires. As one nurse put it: “Being cared for by a tin can, I think that’s a catastrophe, I have to say clearly. If it ever comes to that in nursing homes, I don’t want to work there anymore, and I don’t want to live there either when I’m old” (caregiver, workshop 2). This is not technophobia, but a clear-eyed assessment of what machines cannot perceive: “A technical device cannot recognize when movement is enough. How is the device supposed to detect pain? It just keeps going . . .” (caregiver, workshop 2). At its core, care depends on intuition, empathy, and nonverbal communication; capacities that resist automation. “I don’t believe a robot could replace us . . .  It simply requires feeling, a lot of feeling, and time, time” (caregiver, workshop 2).

Beyond skepticism, care workers voice concrete concerns. New systems bring documentation, training demands, and troubleshooting—tasks that consume precisely the time technology was supposed to free up. “All the paperwork changes too, there are more forms to fill in, and that takes away time from the residents” (caregiver, workshop 1). Surveillance technologies add another layer of anxiety. One caregiver imagined being monitored on the toilet: “It goes ‘pshhhh’ and looks at me; that can also be abused” (caregiver, workshop 2). Underlying these concerns is a deeper fear: that technology will not support relationships but erode them. “With technology you always lose the connection to the resident. It simplifies a lot, but then they are also alone a lot” (care home manager, interview). What emerges is not rejection of technology, but a consistent demand: It should assist, not replace; free up time for relationships, not consume it. “Technology in care would be helpful, but [it should be] always thought together with the caregiver; not: I send a robot and it does what I say, but I am present and have technical support” (caregiver, workshop 1). More fundamentally, care workers call for a shift in perspective: “We can raise awareness that it’s not about what technology we need, but what kind of care we need. And I’m telling you, that is an absolute paradigm shift” (caregiver, workshop 1).

This paradigm shift is political. The voices above are not isolated reactions to technologies in one study. They reflect a consistent pattern that we and our colleagues have documented across more than two decades of qualitative and quantitative research within long-term care settings, through successive generations of “assistive” technology.28 Care workers (residents, and other stakeholders in the care setting) do not change their analysis when a new technology arrives. They keep returning to the same questions, and they are increasingly not alone in asking them. National Nurses United, the largest registered nurses’ union in the United States, surveyed its members in 2024 and found that AI tools “contradict and undermine nurses’ own clinical judgement,” and has called for a moratorium on AI deployment in care settings.[/note]National Nurses United, “National Nurses United Survey Finds A.I. Technology Degrades and Undermines Patient Safety,” May 15, 2024, accessed May 3, 2026, https://www.nationalnursesunited.org/press/national-nurses-united-survey-finds-ai-technology-undermines-patient-safety.[/note] In Germany, ver.di has framed digitalization in care as a labor question, demanding worker participation in technology choices through collective bargaining and works-council agreements.29 When decisions are made by “ladies and gentlemen at the green table” who have never worked a shift on the floor (caregiver, workshop 1), policy becomes disconnected from practice. The question is not only technical but democratic: What kind of care do we, as a society, want to build?

Conclusion

Care robotics will not resolve the care crisis because it does not address its causes. It treats symptoms a faulty diagnosis has made visible, while leaving the diagnosis untouched. A companion robot cannot make a nursing home resident less lonely if the loneliness comes from chronic understaffing. A lifting exoskeleton cannot solve the workforce shortage if the causes are wages and working conditions. The crisis is not a product of demographic inevitability but of political choices: decades of underfunding, marketization, and the treatment of care as a cost rather than a public good. Within this context, robotics functions less as a solution than as a diversion, redirecting attention and resources toward technological optimization while structural reforms remain deferred. The beneficiaries are not care workers or care recipients, but an emerging industry in search of markets.

Reversing this trajectory requires a different set of priorities. Public investment in care must mean rebuilding the care workforce, for example, through wages and working conditions that retain people, training that prepares them, institutional capacity that gives their work the time it needs, the professional autonomy to make care decisions on their own authority, and community-based forms of care. It must mean democratic governance over how care is organized, with clear lines of accountability when technology is brought into the work. And it must mean asking a different question altogether: not which technology to deploy, but what kind of support caregivers and care recipients actually need.

This is not an argument against technology in care, but against a technology that fails the test of who it actually serves. A technology worth funding would have to be shaped, governed, and held accountable by those who give and receive care, and it would have to demonstrate, not assert, that it expands their time, autonomy, and safety. The same logic means accepting that participation can lead to refusal: A care arrangement deciding it does not want the technology on offer is not a failure of the process but the point of it. That, ultimately, is a political question, not a technical one.

The future of care will not be decided in laboratories or innovation hubs. It will be shaped by political struggles over resources, labor rights, and the question at the heart of this debate: What kind of care do we owe one another?

—

Nora Weinberger (Dipl. Ing.) is a researcher at the Institute for Technology Assessment and Systems Analysis at the Karlsruhe Institute of Technology. Her research examines the societal and ethical dimensions of AI, robotics, and digital health, with a focus on care practices and vulnerable groups. She develops participatory approaches to technology assessment and works closely with citizens and stakeholders in real world labs and co design settings.

Dana Mahr (PhD) is a science researcher and technology assessor at the Institute for Technology Assessment and Systems Analysis at the Karlsruhe Institute of Technology (KIT) in Germany. Her work focuses on technology assessment, participatory research, and the social, ethical, and epistemological dimensions of digital health, AI, and science governance. Dana investigates how diverse forms of knowledge shape technological decision-making and contributes to debates on trust, inclusion, and democratic engagement in science and innovation.

Jérémy Lefint (MSc) completed an eight-year apprenticeship in blacksmithing before studying Product Design at HfG Schwäbisch Gmünd and pursuing a Master’s degree in product development. Alongside his studies, he worked as a project leader at a research institute, contributing to the development of ergonomic assistive systems, particularly exoskeletons. Since 2023, he has been a Research Associate at the Institute for Technology Assessment and Systems Analysis (ITAS). His research examines the ethical and social dimensions of assistive technologies, combining design-oriented innovation practice with technology ethics and a focus on user perspectives and societal integration. www.linkedin.com/in/jérémy-lefint-51a694147

Bettina-Johanna Krings (Dr. phil) is a sociologist and works as Senior Scientist at the Institute of Technology Assessment and Systems Analysis (ITAS) and Lecturer at KIT. Her scientific focus lies on the one hand on the relationship of new technologies and employment (organization, profession, labor market). On the other hand, she is specialized in Human-Machine-Interaction in Technology Assessment with focus on health care and transformation research. Her theoretical back is Critical Theory.

Notes

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  3. Corporate Europe Observatory and European Federation of Public Service Unions, When the Market Becomes Deadly: How Pressures towards Privatisation of Health and Long-Term Care Put Europeans’ Lives at Risk (2021), https://corporateeurope.org/sites/default/files/2021-01/healthcare-privatisation-final.pdf.
  4. Manfred Hülsken-Giesler, “Pandemie trifft Pflegenotstand” [Pandemic meets the nursing shortage], Intensiv 28, no. 3 (2020): 122–25.
  5. European Commission, Horizon Europe Work Programme 2023–2025, chap. 4, “Health,” Decision C(2024) 2371 (April 17, 2024).
  6. Corporate Europe Observatory and EPSU, When the Market Becomes Deadly.
  7. European Commission, Health and Long-Term Care in the European Union, Special Eurobarometer 283/Wave 67.3 (European Commission, 2007).
  9. OECD, Beyond Applause? Improving Working Conditions in Long-Term Care (OECD Publishing, 2023), 4, https://doi.org/10.1787/27d33ab3-en. Meanwhile, the long-term care crisis has only intensified as reforms across Europe shifted responsibility back onto families instead of expanding public provision.8Ellen Verbakel et al., “Indicators of Familialism and Defamilialization in Long-Term Care: A Theoretical Overview and Introduction of Macro-Level Indicators,” Journal of European Social Policy 33, no. 1 (2023): 35, https://doi.org/10.1177/09589287221115669.
  10. Thomas Gerlinger, “Long-Term Care Insurance in Germany: Facing a Paradigm Shift in Financing?,” ESPN Flash Report 2020/63 (European Social Policy Network, European Commission, 2020), 1, https://ec.europa.eu/social/BlobServlet?docId=23304&langId=en.
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  13. Care4Care, Care Workers, Job Quality, and Inclusive Working Conditions, German National Report (Brussels, 2023), 47.
  14. Care4Care, Care Workers, 47.
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  16. OECD, Beyond Applause?, 27.
  17. Santiago Quesada-García, “Ageing and Ambient Assisted Living: New Landscapes of Dwelling,” in Ageing and Urban Planning, ed. Matthias Drilling, Pamela Suero, Hind Al-Shoubaki, and Fabian Neuhaus (Routledge, 2025), https://doi.org/10.4324/9781003144441-7.
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  19. Gianluca Bardaro et al., “Robots for Elderly Care in the Home: A Landscape Analysis and Co-Design Toolkit,” International Journal of Social Robotics 14 (2022): 657–81, https://doi.org/10.1007/s12369-021-00816-3; Goran Roos, “Living Labs as Innovation Catalysts in the Silver Economy: Co-Creating Solutions for Ageing in Place,” in Economic Transformations in Population Aging: Unlocking the Silver Economy, ed. Zyed Achour and Ihsen Abid (IGI Global Scientific Publishing, 2026), 89–146, https://doi.org/10.4018/979-8-3373-6117-8.ch004.
  20. Evelyn Nakano Glenn, “Forced to Care: Coercion and Caregiving in America” (Harvard University Press, 2010): 4–9; Harry Braverman, Labor and Monopoly Capital: The Degradation of Work in the Twentieth Century, 25th ed.(Monthly Review Press, 1998): 56–57, 137–38.
  21. Giovanni L. Masala and Ilaria Giorgi, “Artificial Intelligence and Assistive Robotics in Healthcare Services: Applications in Silver Care,” International Journal of Environmental Research and Public Health 22, no. 5 (2025): 781, https://doi.org/10.3390/ijerph22050781; Mahdi Karimi and Saeed Yazdani, “Utilizing Robotics in Health Care: Increasing the Efficiency and Accuracy of Patient Therapy,” Journal of World Future Medicine, Health and Nursing 3, no. 2 (2025): 172–82, https://doi.org/10.70177/health.v3i2.1909; Lea Farah et al., “Assessment of Exoskeletons on Nurses’ Quality of Work Life: A Pilot Study at Foch Hospital,” Nursing Reports 13 (2023): 780–91, https://doi.org/10.3390/nursrep13020068.
  22. All transcripts and field observations drawn from a workshop series and individual interviews conducted as part of the project MOVEMENZ. Parenthetical attributions indicate the speaker’s role and the data collection setting. Transcripts and field notes on file with the first author.
  23. Tamara Backhouse et al., “How Do Family Carers and Care-Home Staff Manage Refusals When Assisting a Person with Advanced Dementia with Their Personal Care?,” Dementia 21, no. 8 (November 2022): 2458–75, https://doi.org/10.1177/14713012221123578; Alison Kitson et al., Reclaiming and Redefining the Fundamentals of Care: Nursing’s Response to Meeting Patients’ Basic Human Needs (School of Nursing, University of Adelaide, 2013); Maximilian Bubeck et al., “An Interview Study on Socially Assistive Robots and Professional Care Relationships,” Nursing Ethics (2025), https://doi.org/10.1177/09697330251385025.
  24. Jeannette Pols, “Good Relations with Technology: Empirical Ethics and Aesthetics in Care,” Nursing Philosophy 18, no. 1 (2017), https://doi.org/10.1111/nup.12154.
  25. Trisha Greenhalgh et al., “Beyond Adoption: A New Framework for Theorizing and Evaluating Nonadoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies,” Journal of Medical Internet Research 19, no. 11 (2017): e367, https://doi.org/10.2196/jmir.8775.
  26. Bettina-Johanna Krings and Nora Weinberger, “Technology or Practices of Care First? Technology Assessment in the Tension Between ‘Technology Push’ and Managing Socio-Technological Futures,” TATuP – Zeitschrift für Technikfolgenabschätzung in Theorie und Praxis 34, no. 1 (2025): 28–34, https://doi.org/10.14512/tatup.7167.
  27. Yucheng Cao et al., “Ethical Challenges in the Algorithmic Era: A Systematic Rapid Review of Risk Insights and Governance Pathways for Nursing Predictive Analytics and Early Warning Systems,” BMC Medical Ethics 26 (2025): 151, https://doi.org/10.1186/s12910-025-01308-z; Lisa Tessman, “Moral Distress in Health Care: When Is It Fitting?,” Medicine, Health Care and Philosophy 23, no. 2 (2020): 165–77, https://doi.org/10.1007/s11019-020-09942-7.
  28. Nora Weinberger and Michael Decker, “Technische Unterstützung für Menschen mit Demenz? Zur Notwendigkeit einer bedarfsorientierten Technikentwicklung” [Technical support for people with dementia? On the necessity of needs-oriented technology development], Technikfolgenabschätzung – Theorie und Praxis 24, no. 2 (2015): 36–45; Tobias Moeller et al., “Von Disziplinär zu Interdisziplinär: Vier Perspektiven auf Bewegungsförderung in Pflegeeinrichtungen mit digitalen Technologien” [From disciplinary to interdisciplinary: Four perspectives on movement promotion in care facilities with digital technologies], Pflege & Gesellschaft 30, no. 3 (2025): 217–31, https://doi.org/10.3262/pug2503217; Nora Weinberger et al., “From an Ethics of Deficiency to an Ethics of Abundance: Convivial Technologies in Care,” TATuP – Zeitschrift für Technikfolgenabschätzung in Theorie und Praxis 34, no. 3 (2025): 15–20, https://doi.org/10.14512/tatup.7183.
  29. ver.di, “Digitalisierung und was sie für Arbeitnehmer bedeutet” [Digitalization and what it means for workers], accessed May 3, 2026, https://www.verdi.de/politik-gesellschaft/digitalisierung-und-was-sie-fuer-arbeitnehmer-bedeutet.