Robotic systems have great potential to improve medical care, but their integration by non-technical staff remains a challenge. LLMs open up new possibilities for human-robot interaction, but they also harbor risks such as misinterpretation, bias, and safety issues. The 新万博体育下载_万博体育app【投注官网】 of Augsburg's subproject systematically investigates the risks associated with the use of LLMs and LC/NC mechanisms based on them in nursing care.

The aim is to advance methods for early risk detection and optimization of language models and to promote their application in the Module 1 projects. To raise awareness among nursing staff, practical test scenarios are being developed, tested, and evaluated in a real-world laboratory. The insights and methods gained contribute to the improvement of existing systems and support the safe, transparent use of LLMs in healthcare robotics.

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