Assessing Awareness of Ethical Utilization of Artificial Intelligence in Education Insights from Faculty Staff and Medical Students

Background: Artificial Intelligence (AI) is increasingly reshaping healthcare delivery and medical training through its capacity to simulate cognitive processes such as learning, reasoning, and problem-solving. As its applications expand, particularly in clinical decision-making and academic environments, ethical concerns surrounding AI such as data privacy, algorithmic bias, and accountability have become critical. Objectives: This study aimed to appraise awareness, educational exposure, and e ethical perspectives on AI utilization among faculty staff and Faculty of Medicine students, Zagazig University. Methods: A cross-sectional study was conducted at the Faculty of Medicine, Zagazig University, involving 327 participants (82 faculty staff and 245 students). A structured questionnaire was used to evaluate participants' understanding of AI technologies and ethical considerations. Data were analyzed using IBM SPSS version 25. Categorical variables were compared using Chi-square or Fisher’s exact test, with a significance at p < 0.05. Results: Medical students demonstrated significantly higher levels of AI awareness and formal educational exposure compared to faculty staff (p < 0.001). While 60% of students had received AI training, only 29.3% of faculty reported the same. Students primarily learned through formal coursework, whereas faculty relied predominantly on social media. Despite 100% faculty and 86.5% student recognition of AI's presence in medicine, both groups exhibited limited understanding of AI’s ethical implications. Concerns about job displacement and trust in AI tools were noted, particularly among students. Both groups strongly advocated for embedding AI-related topics, including ethics, as a part of medical curriculum. Conclusion: The study revealed generational and professional disparities in AI literacy and ethical readiness. While students showed greater receptiveness, faculty required targeted continuing education. Medical institutions should integrate structured AI and ethics education into medical curricula while also providing continuous professional development for faculty. This dual approach will ensure both students and educators are competent to integrate AI into healthcare practice while upholding ethical standards.