Ethical and Practical Considerations of Physicians and Nurses on Integrating Artificial Intelligence in Clinical...

Background/Objectives: The emergence of artificial intelligence (AI) has revolutionized the healthcare industry. However, its integration into clinical practices raises ethical and practical concerns. This study aims to explore ethical and practical considerations perceived by physicians and nurses in Saudi Arabia. Methods: It employed a cross-sectional design with 400 physicians and nurses, using a pre-established online questionnaire. Descriptive data were analyzed through means and standard deviations, while inferential statistics were performed using the independent samples t-test. Results: Most participants were male (57%) and physicians (73.8%), with most employed in governmental organizations (87%). The participants' use and awareness of AI was low, as 34.0% said they had never used it, but 74.5% of respondents were willing to use AI in clinical practices. Also, 80.5% of participants were aware of the AI benefits, and 71.0% had background knowledge about the ethical concerns related to AI's implementation in their clinical practices. Moreover, (62.0%) of respondents recognized the applicability of AI in their specialty. Key findings revealed significant concerns: participants perceived a lack of skills to effectively utilize AI in clinical practice (mean = 4.04) and security risks such as AI manipulation or hacking (mean = 3.83). The most pressing ethical challenges included AI's potential incompatibility with all populations and cultural norms (mean = 3.90) and uncertainty regarding responsibility for AI-related errors (mean = 3.84). Conclusions: These findings highlight substantial barriers that hinder the effective integration of AI in clinical practices in Saudi Arabia. Addressing these challenges requires leadership support, specific training initiatives, and developing practical strategies tailored to the local context. Future research should include other healthcare professionals and qualitatively explore further underlying factors influencing AI adoption.