Care in the Age of ‘Intelligent’ Systems

Across aging societies, health and care systems are under growing pressure. Some governments have positioned technology as both a solution and a necessity to tackle labor shortages, rising health and care costs, and demographic shifts. AI-driven monitoring systems, care robots, and digital assistants are increasingly framed as tools that can help sustain care infrastructures at scale.

Yet care is not merely a logistical or technical problem. It is relational, emotional, and embedded in social and cultural contexts. The integration of so-called intelligent systems into care therefore raises deeper questions—not only about efficiency and capability, but about responsibility, dignity of the person being cared for, and the meaning of care itself.

The Performance of Technological Futures

A significant tension lies in the gap between how care technologies are presented and how they function in practice. In robotics laboratories, technologies are often demonstrated under carefully controlled conditions. Laboratories are optimized to ensure smooth operation: obstacles are removed, lighting is calibrated, and systems are continuously monitored.

These demonstrations create illusions of autonomous and reliable machines. However, they often rely on hidden layers of human intervention—engineers adjusting systems in real time or partially controlling outcomes. What appears as seamless automation is frequently a coordinated performance (De Togni, 2024).

When these staged demonstrations are taken as evidence of real-world readiness, they shape expectations in ways that obscure the limitations of current technologies. Outside controlled environments, care settings—homes, hospitals, and assisted living facilities—are far more complex and unpredictable. They involve not only physical variability but also interpersonal dynamics and emotional labor that resist standardization.

Care Beyond Efficiency

The persistence of optimistic narratives around care technologies reflects broader political and economic dynamics. Technological promises attract investment, justify policy priorities, and reinforce national ambitions for innovation and competitiveness. In some contexts, care technologies are framed not only as practical tools but as symbols of progress and future readiness (De Togni, 2026).

At the same time, alternative approaches to care—such as improving working conditions for caregivers or strengthening social support systems—receive comparatively less attention. Care is reframed as a problem of efficiency, coordination, and data management, rather than one of labor, structural inequalities, or social responsibility.

This reframing risks overlooking the fundamental nature of care. Care involves empathy, trust, responsibility, and human connection. While technologies may assist with certain tasks, they cannot replace the relational and ethical dimensions that define care practices (De Togni, 2025).

The Datafication of Aging and Care

The design of care technologies is also shaped by underlying assumptions about aging. Older adults are frequently represented as passive, dependent, or technologically resistant. These assumptions are embedded in datasets, design processes, and implementation strategies.

As care becomes increasingly mediated by digital systems, it is often reduced to measurable indicators: dashboards, alerts, and monitoring tools. Individuals are translated into data points—signals of risk, decline, or deviation. This process of datafication simplifies complex lived experiences into quantifiable variables, obscuring the broader contexts in which care takes place.

The limitations of this approach become evident in practice. For instance, fall detection systems—widely promoted as safety solutions—are often trained on datasets that do not accurately reflect different bodies and real care environments. The resulting systems may produce frequent false alarms, leading users and caregivers to mistrust and ultimately ignore them. In such cases, technology does not adapt to human needs; instead, people either have to adapt their practices to accommodate the technology or see the device as an obstacle to the provision of care.

Beyond Technosolutionism

These patterns reflect a broader tendency toward technosolutionism—the belief that complex social problems can be addressed primarily through technological innovation. While care systems undeniably face structural challenges, reducing these challenges to technical issues risks ignoring their social, political, and ethical dimensions.

Care is shaped by institutional arrangements, labor conditions, cultural norms, and power relations. Technological interventions developed without attention to these factors may reproduce existing inequalities or introduce new forms of exclusion.

Toward Inclusive and Responsible Innovation

A more inclusive approach to care technologies requires rethinking how innovation is defined and practiced. Meaningful engagement with care workers, caregivers, and care recipients must occur early in the design process, rather than as a symbolic or late-stage exercise.

Such engagement also requires acknowledging that different stakeholders have distinct—and sometimes conflicting—needs. Rather than seeking simple consensus, inclusive design must create space for negotiation, recognize power imbalances, and value diverse forms of expertise, including lived experience (De Togni et al., 2026).

Equally important is the recognition of limits. Not all problems demand technological solutions, and not all technological possibilities are ideal for certain contexts and actors. Responsible innovation includes the capacity to question, redirect, or even halt development when necessary.

Reimagining Care Futures

Alternative models of care technology suggest that more inclusive futures are possible. When technologies are co-designed with users and embedded meaningfully in social contexts, they can support autonomy, participation, and connection. In some cases, they enable individuals who might otherwise be excluded—such as those with severe physical disabilities—to engage, if they wish to do so, in work and community life activities in new ways.

These examples point toward a different understanding of innovation: one that prioritizes enrichment over optimization, and relationships over efficiency.

Conclusion

The integration of AI and robotics into care systems presents both opportunities and risks. While technologies may help address certain challenges, they cannot alone sustain or resolve emerging needs in strained health and care systems.

The critical question is not simply whether technology can improve care, but how care itself is being reshaped in the process. Who defines the problems to be solved? Whose voices are included and whose are excluded in the process? And what values are embedded in the systems being built?

The future of care will depend not only on technological advancement, but on the choices societies make about how to tackle structural inequalities and foster collective responsibility for care. In this sense, care is not just a site of innovation—it is a site of negotiation about the kind of future we collectively want to create.

References

• De Togni, G. (2024). Staging the robot: Performing techno-politics of innovation for care robotics in Japan. East Asian Science, Technology and Society: An International Journal, 18(2), 196-213. https://doi.org/10.1080/18752160.2023.2295144Article
• De Togni, G. (2025). Hearts meet wires: Navigating the ethical and social implications of care robotics. In E. Giannoulis & B. Frommann (Eds.), The future of humans and emotional machines: Narratives from Japanese culture in the 21st century (pp. 49-63). Routledge. https://doi.org/10.4324/9781003570653Article
• De Togni, G. (2026). Intelligent and caring robots by 2050? Narratives and future orientations for technocare in Japan. Contemporary Japan. https://doi.org/10.1080/18692729.2026.2612808Article
• De Togni, G., Catanzariti, B., Christou, A., Constantin, A., Jeon, C., Jokinen, K., Romeo, M., Shin, H., Smit, S. L., Spoden, C., Søraa, R. A., Vijayakumar, S., Wang, M. Z., Wiggert, K., & Williams, R. (2026). REALIGN Toolkit: Reflexivity, adaptability, leadership, and inclusion as pillars of responsible research and innovation. Wellcome Open Research, 11, Article 8. https://doi.org/10.12688/wellcomeopenres.25459.1Article

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