Possibilities and ethical issues of entrusting nursing tasks to robots and artificial intelligence
This academic paper examines the ethical possibilities and challenges of entrusting nursing tasks to robots and artificial intelligence. It focuses on four core ethical nursing concepts—advocacy, accountability, cooperation, and caring—analyzing whether and how they might be implemented in robotic systems. The authors conclude that while implementing certain technical or safeguarding aspects is feasible, deeper emotional and relational components present significant philosophical and practical hurdles requiring broad societal discussion.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
This paper should be read by researchers, ethicists, healthcare professionals, and technologists interested in the intersection of artificial intelligence, robotics, and nursing ethics.
What the document contains
The document addresses the feasibility and ethical implications of incorporating robots and AI into nursing practice by analyzing four key ethical concepts: advocacy, accountability, cooperation, and caring. It evaluates current technological capabilities in healthcare robotics and outlines potential social, economic, and existential concerns regarding their deployment.
The text does not provide binding regulatory standards, legal frameworks, or enforceable guidelines for deploying nursing robots, nor does it offer a definitive consensus on whether such technologies should ultimately be integrated into clinical care.
- Nursing tasks involving physical transport, vital monitoring, and fall prevention are increasingly feasible for robots and AI.
- Elements of patient advocacy like safeguarding and apprising are relatively easy to implement, whereas valuing and mediating require emotional communication that is difficult for machines.
- Explainable AI can support accountability, but it faces problems of infinite regression, attribution of responsibility, and epistemic limitations.
- Cooperation requires recognizing robots as community members, though physical appearance must carefully navigate the uncanny valley effect.
- Caring involves complex dimensions where care-receiving and emotional connection present distinct challenges that require ongoing empirical and philosophical research.
· Introduction · Background · Advocacy: can robots and artificial intelligence be a voice and advocate for patients? · Accountability: can robots and artificial intelligence take responsibility for their actions? · Cooperation: can robots and artificial intelligence collaborate with other healthcare professionals? · Caring: can robots and artificial intelligence become care-providing entities? · Discussion: How can artificial intelligence and robots be introduced sustainably in the nursing process? · Summary
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
3/5Clear responsibility for AI outcomes
Accountability: Robotic nurses with explainable AI have a certain level of accountability. However, the concept of explanation has problems of infinite regression and attribution of responsibility.
Abstract
screening score · 2026-10-24
Fairness
0/5Non-discrimination and equitable treatment
N/A
screening score · 2026-10-24
Human Dignity
2/5Respect for the inherent worth of persons
For example, Sparrow describes a scenario in which an elderly person with dementia endlessly repeats the same story to a care robot—a tragic example of how care for the elderly can be entrusted to robots.
Discussion
screening score · 2026-10-24
Human Oversight
0/5Humans remain in control of consequential decisions
N/A
screening score · 2026-10-24
Privacy
0/5Protection of personal data and private life
N/A
screening score · 2026-10-24
Transparency
3/5Openness about how AI systems work and are used
Various types of explainable AI are currently being developed to challenge the black box of deep learning, and the methods of explanation are mixed, including those that explain perceptively and mathematically.
Accountability
screening score · 2026-10-24
Enforcement
0/5Consequences and compliance mechanisms with real force
N/A
screening score · 2026-10-24
Impact Assessment
1/5Required assessment of an AI system's risks/impacts before or during use
Although a more detailed cost–benefit analysis is needed, considering the cost of creating a single nursing robot and its maintenance, it may be far more realistic to train and employ a new nurse.
Discussion
screening score · 2026-10-24