Care ethics and the transformation of care in an age of artificial intelligence

BACKGROUND: The integration of artificial intelligence (AI) and care robots into healthcare raises a central ethical question: what constitutes care, and how should it be delivered when machines perform caregiving tasks? Dominant AI ethics frameworks, including principlism, deontology, and consequentialism, focus on fairness, duties, and outcomes. While important, these approaches often view care primarily as technical compliance or efficiency, overlooking its relational and evaluative aspects. METHODS: This analysis employs a normative, conceptual approach rooted in care and relational ethics, examining duty-based, outcome-oriented, and virtue-based care frameworks to highlight how they differ from care ethics as a structured moral practice. Tronto's four stages of care (attentiveness, responsibility, competence, and responsiveness) serve as a framework for assessing moral labor in caregiving. Literature on social robots in healthcare is used illustratively. Conceptual analysis compares the interpersonal and moral dimensions of human caregiving with forms of AI interaction, noting changes when machines mediate or perform caregiving tasks. RESULTS: The analysis shows that although AI systems can improve monitoring, coordination, and task performance, they do not assume moral responsibility or provide the relational and evaluative work that caregiving requires. Social and assistive robots reorganize moral labor by shifting attentiveness toward sensing, responsibility toward oversight, competence toward optimization, and responsiveness toward adaptive feedback. These changes create a functional resemblance to care without reproducing the moral engagement that characterizes genuine caregiving. CONCLUSION: Care ethics elucidates the moral practices of caregiving and how these practices are transformed through the integration of AI into healthcare relationships. Since caregiving involves vulnerability, interdependence, and judgment, it cannot rely solely on efficiency. A care-ethical perspective demonstrates that AI does not replace moral labor; rather, it reorganizes it in ways that reduce the conditions under which authentic caregiving can be conducted. The incorporation of care ethics into AI governance frameworks provides tools for assessing not just what these technologies do but what they cost the moral practice of caregiving.

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Publication Details

Journal
BMC Medical Ethics
Published
2026-05-30
DOI
https://doi.org/10.1186/s12910-026-01474-8
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

Care ethics and the transformation of care in an age of artificial intelligence

Rachel Wangari Kimani
BMC Medical Ethics
Ethics and Social Impacts of AI
article

Care ethics and the transformation of care in an age of artificial intelligence

Rachel Wangari Kimani
article en

Abstract

BACKGROUND: The integration of artificial intelligence (AI) and care robots into healthcare raises a central ethical question: what constitutes care, and how should it be delivered when machines perform caregiving tasks? Dominant AI ethics frameworks, including principlism, deontology, and consequentialism, focus on fairness, duties, and outcomes. While important, these approaches often view care primarily as technical compliance or efficiency, overlooking its relational and evaluative aspects. METHODS: This analysis employs a normative, conceptual approach rooted in care and relational ethics, examining duty-based, outcome-oriented, and virtue-based care frameworks to highlight how they differ from care ethics as a structured moral practice. Tronto's four stages of care (attentiveness, responsibility, competence, and responsiveness) serve as a framework for assessing moral labor in caregiving. Literature on social robots in healthcare is used illustratively. Conceptual analysis compares the interpersonal and moral dimensions of human caregiving with forms of AI interaction, noting changes when machines mediate or perform caregiving tasks. RESULTS: The analysis shows that although AI systems can improve monitoring, coordination, and task performance, they do not assume moral responsibility or provide the relational and evaluative work that caregiving requires. Social and assistive robots reorganize moral labor by shifting attentiveness toward sensing, responsibility toward oversight, competence toward optimization, and responsiveness toward adaptive feedback. These changes create a functional resemblance to care without reproducing the moral engagement that characterizes genuine caregiving. CONCLUSION: Care ethics elucidates the moral practices of caregiving and how these practices are transformed through the integration of AI into healthcare relationships. Since caregiving involves vulnerability, interdependence, and judgment, it cannot rely solely on efficiency. A care-ethical perspective demonstrates that AI does not replace moral labor; rather, it reorganizes it in ways that reduce the conditions under which authentic caregiving can be conducted. The incorporation of care ethics into AI governance frameworks provides tools for assessing not just what these technologies do but what they cost the moral practice of caregiving.

BMC Medical Ethics
Binghamton University (US), University of Manchester (GB)
Decent work and economic growth
Openalex Percentile: Top 4%
Ethics and Social Impacts of AI
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