YuLei Song

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About

YuLei Song is a forward-thinking researcher at the intersection of healthcare, artificial intelligence, and ethics. Her work critically examines the integration of intelligent systems into nursing and health education, with a particular focus on the ethical implications of robot-assisted care. Song’s most cited study, "Ethical risks in robot health education: A qualitative study" (2024), has already garnered 9 citations, reflecting growing interest in her pioneering analysis. In this work, she applies the European Union’s "Responsible Research and Innovation" (RRI) framework to uncover hidden ethical risks in deploying robots for patient education—a vital yet underexplored area. By combining qualitative methods with a deep understanding of nursing practice, Song highlights how automation can inadvertently compromise patient autonomy, privacy, and trust. Her contributions are especially timely as healthcare systems worldwide accelerate digital transformation. Song’s research not only identifies critical challenges but also offers a roadmap for designing ethically responsible health technologies. For students and researchers in health informatics, nursing ethics, or human-robot interaction, her work serves as an essential guide to balancing innovation with human-centered care.