Paper interpretation | Harnessing the integration of artificial intelligence in nursing: Opportunities, challenges, and strategic actions

 In recent years, Artificial Intelligence (AI) has triggered changes in various fields such as healthcare, and it has the potential to revolutionize traditional models, optimize the learning experience, and improve patients' prognosis in nursing practice, education, and research, but in the actual integration process, it is facing the problems of possible replacement of nursing positions, insufficient AI competence of nurses, and ethical dimensions such as data privacy protection and algorithmic bias.

 Based on this, Rick Yiu Cho Kwan et al. from Tung Wah College, Hong Kong, published an article titled "Navigating the integration of artificial intelligence in nursing: Opportunities and opportunities" in the International Journal of Nursing Sciences. The article explores the opportunities of artificial intelligence in nursing practice, education and research, analyzes the challenges of potential replacement of human roles, lagging AI capabilities and ethical issues, and proposes to re-invest in the humanities. It also analyzes challenges such as the potential replacement of human roles, lagging AI capabilities, and ethical issues, and proposes strategic actions such as reinvesting in humanistic practices, revising core competencies and curricula, and developing new ethical guidelines.

 AI is profoundly changing the nursing profession, demonstrating a duality in clinical practice, education, and research: it offers both possibilities for innovation and multiple challenges. On the one hand, technology empowers nursing innovation. In clinical practice, AI improves nursing accuracy through early disease detection and decision support. For example, AI algorithms assist in the diagnosis of skin diseases, enabling doctors and nurses to improve diagnostic accuracy; wound care chatbots provide standardized guidance for non-professionals, with content validity at a satisfactory level. In the field of education, tools such as virtual avatars and AI-driven simulation systems optimize the learning experience; AI doctors in sepsis care training are comparable to real-life simulations, and generative AI (e.g., ChatGPT) also assists academic writing and personalized learning. In terms of research, AI accelerates data modeling and analysis, mines patterns that are difficult for humans to identify from massive data, and improves scientific research efficiency.

 On the other hand, there are real-life dilemmas in human-machine collaboration. the potential replacement of nursing positions by AI has sparked controversy. Some nurses worry that automation leads to dehumanization, while managers mostly believe that AI cannot replace the emotional connection of human nursing. Professional competence disconnect is prominent, with nursing teachers having the strongest AI skills and students the weakest, and the lack of AI training in the curriculum makes it difficult for graduates to adapt to a technology-driven clinical environment. Ethical risks cannot be ignored, with issues of data privacy, algorithmic bias and attribution of responsibility for decision-making needing to be addressed, such as AI exacerbating the unequal distribution of healthcare resources and the lack of legal accountability mechanisms for wrong decisions.

 Therefore, the article proposes a systematic countermeasure to build a human-machine symbiosis system. First, it is necessary to balance technical efficiency and humanistic care, strengthen nurses' ability in irreplaceable areas such as communication and empathy, and position AI as an auxiliary tool rather than a substitute. Second, educational reform should not be delayed, incorporating AI operational skills into core competencies, developing interdisciplinary courses in conjunction with computer science and other fields, and enhancing students' AI literacy from theory to practice. Finally, refer to the ethical frameworks of the American Nurses Association and the European Union to develop industry guidelines covering data security and transparent decision-making, and clarify the legal boundaries of AI applications.

 In summary, the integration of AI and nursing is an inevitable trend. The only way to unleash the potential of AI and promote the nursing industry to realize high-quality development in the technological wave is to strengthen the humanistic roots, make up for the shortcomings of skills, and improve the ethical framework.