Abstract
Rapid recent advances in information technology have opened the door for artificial intelligence (AI)-related technologies to be applied extensively across many industries. The Ministry of Education has emphasized the importance of cultivating advanced-level professionals in diverse fields, particularly in smart machinery, the Asia-Silicon Valley sector, green energy technology, biotechnology, national defense, new agricultural, and circular economy industries, to enhance innovation and promote industrial competitiveness (Kuo, 2019). While interdisciplinary talent in AI and digital innovation is being actively developed elsewhere, nursing education remains in the exploratory phase of AI and digital technology talent cultivation. Although AI is now a well-known term, the competencies required for its application in nursing remain unclear. Moreover, most nursing professionals are unfamiliar with how to best integrate AI into nursing expertise or practice settings. With the application of AI in the healthcare industry now unstoppable, it is vital to consider how to help nursing students adapt to healthcare's new technology landscape (Huang et al., 2021). AI facilitates the digital simulation of human thought patterns, logic, and behaviors with the goal of assisting human users solve problems, especially those that are time-consuming and require repetitive processing. The development of AI requires interdisciplinary collaboration among domain experts, data scientists, software engineers, robotics experts, and computer programmers. Such collaboration is essential to developing products able to meet the demands of the times and to help students become competent future nursing professionals (Murray, 2018). Nurses spend the most time interacting with patients and are thus best able to understand the perceptions and challenges of patients and their families. Collaborating with professionals from interdisciplinary fields is the best strategy for achieving optimal healthcare outcomes. However, nursing schools have yet to provide a clear response to the impact of AI on nursing education. Nursing educational institutions must enable nursing students to comprehend the concepts and principles of AI and equip them with AI literacy to allow them to unleash their potential, continuously innovate, and stay abreast with the times (Ng et al., 2021). In this issue, experts and scholars currently engaged in AI-related research in the nursing discipline share their research findings in the realms of machine learning, deep learning, emotional recognition, and natural language application. These articles offer insights into the implications of AI, suggest how nursing education may best respond to emerging AI trends, and provide the authors' perspectives on nursing education reform. The editor hopes readers will be inspired to explore new concepts, gain a deeper understanding of the application and significance of AI, and apply AI to address clinical and educational challenges to foster competent nursing professionals for tomorrow.
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