Laypeople in nursing repeatedly use the misleading term “care robots” in articles and books. This gives readers the impression that the machines provide care, perhaps even replacing nursing professionals. This is false, as Alice Lin, Director of UX/UI Design at Hon Hai Technology Group (Foxconn), makes clear in an interview.
Terms like clinical assistant robot or collaborative robot (cobot) are far more appropriate. These intelligent helpers take on transport and delivery tasks, can perform simple routine tasks, and inform nursing professionals when they are needed more urgently than usual. They do not provide care to people—not even the most advanced models do so yet.
This is neither meant to diminish the services provided by service robots nor to question their importance. Nurses, in particular, are highly encouraged to have tasks that are not directly related to patients completed without taking up their already limited time. The expertise of nursing professionals belongs to the people who need it. This requires time that should not be wasted on pick-up and drop-off services. In short: robots are there to provide care—but they do not provide care. Whether this will ever change remains to be seen. What is certain, however, is that the term “care robot” often used in this country is misleading.
Interview with Alice Lin (Foxconn):
The so-called Nurabot uses AI models and digital twin training and is currently being used in pilot projects at Smart Hospital Taiwan. However, its full potential in everyday clinical practice will only become apparent after comprehensive field studies and widespread practical use in various institutions.
Jochen Gust: What specific tasks can the Nurabot currently perform in hospitals or care facilities, and how does it interact with staff and patients?
Alice Lin: The Nurabot is currently undergoing clinical trials on ward W106 of the Taichung Veterans General Hospital in Taiwan (according to Newsweek 2025, the hospital is one of the 100 best smart hospitals in the world). It is a collaborative service robot that is particularly used for recurring logistical tasks in everyday clinical practice, such as delivering medications and samples, detecting excessive ambient noise, and also has audio and wayfinding functions that help patients find their way around the ward. This improves patient orientation and their sense of security during their hospital stay. The Nurabot interacts with medical staff via voice prompts, touchscreen, and a cloud-based dispatch system. It behaves friendly and gently towards patients and provides medication, care, and discharge instructions. The robot asks simple, standardized questions about the patient’s current condition to support nursing staff with routine documentation.
Thanks to its multimodal AI perception system and real-time positioning and navigation functions, the robot can autonomously plan routes, avoid obstacles, and move safely in dynamic and busy environments. The goal of the design is not to replace human interaction, but to relieve nursing staff of repetitive logistical tasks, leaving more time for complex and emotional care.
Currently no focus on people with dementia
Jochen Gust: Are there any use cases or pilot projects with people with dementia? What observations or challenges have arisen?
Alice Lin: Nurabot’s initial focus is on its role as a collaborative service robot. Only ten months passed from development to pilot operation, and a test has been running since April 2025 and will last until the end of 2025. The first deployment will take place on one of Taiwan’s busiest wards, W106 with 68 beds, responsible for pulmonology and oral and maxillofacial surgery (including lung cancer, COPD, asthma).
Using digital twin technology, the ward was virtually mapped in advance, minimizing 80% of potential risks before real-life operations. Our practical experience has shown that the Nurabot’s “safe” design, calm movements, and gentle speech help reduce fear and shock reactions in elderly patients. The robot does not come into direct physical contact with patients, but rather supports nursing staff – for example, by providing health information via audio-video format. This accompanying role promotes trust. Targeted studies for patients with dementia are also planned for the future. However, this is not currently our focus.
Jochen Gust: To what extent were nurses and other hospital employees involved in the development and testing?
Alice Lin: Our starting point was the real daily work of nursing staff. A nurse walks over 10,000 steps a day – much of which is spent running errands alone. The hospital management and nursing staff were open to innovation. Our UX team interviewed and accompanied the ward managers and nurses on W106 at work to identify the most time-consuming and monotonous activities. These insights were directly incorporated into the functional design: medication and sample delivery, material supply, and health videos. During the design phase, the nursing staff helped with route planning and simulating real-life workflows. The Foxconn team also made continuous adjustments during the testing phase.
Nursing professionals therefore played a key role in making the Nurabot practical, suitable for everyday use, and accepted. We also worked closely with Kawasaki Heavy Industries and NVIDIA on the technical side.
Jochen Gust: What long-term role do you see for the Nurabot—as a supplement to, or as a means of automating, even complex tasks?
Alice Lin: The goal is to make the healthcare system more resilient by taking over repetitive, stressful tasks to relieve the burden on nursing staff. As AI advances, Nurabot will increasingly take on more demanding tasks, but always in the spirit of “human-machine collaboration.” It’s intended to support caregivers, not replace them. The emotional and empathic work remains the responsibility of the human.
Jochen Gust: Are there concrete plans for a rollout in Europe or Germany?
Alice Lin: Digital health is one of Foxconn’s three strategic future fields (along with robotics and e-mobility). The core technologies are semiconductors, AI, and new communication systems. Market entry in Europe, especially Germany, is being actively explored. However, this would require, among other things, testing in partner clinics, CE certification, and the establishment of service and maintenance structures in accordance with local requirements. Costs vary depending on the scale of deployment, range of functions, and service contracts.
