Artificial Intelligence Literacy among Medical Students: A Cross-Sectional Study of Knowledge, Usage, and Ethical Awareness

Abstract

The time of artificial intelligence (AI) is now in training and altering both medical education and healthcare; thus, the demand for a thorough knowledge of how future doctors see and deal with this new technology is increasing. This study was carried out to determine medical students' attitudes, self-reported knowledge, usage patterns, and training needs regarding AI in the context of undergraduate medical education. A cross-sectional descriptive study was done at the College of Medicine, Al-Iraqia University, with a self-administered questionnaire drawn from a review of current literature being distributed to undergraduate medical students across all academic years. Data were analyzed using SPSS version 29. Descriptive statistics and chi-square tests were applied to explore relationships between variables.

Out of 850 invited students, 199 completed the questionnaire (response rate: 23.5%). Most respondents were female (57.3%), while the mean age was 20.73 years (SD ±1.85). It is worth mentioning that 45.2% of students had a background knowledge of AI, but only 10.1% could deliver a detailed explanation. AI tools were utilized by 89.9% of the participants at least once per month. High interest rates of students in AI-related training topics were recorded mainly in clinical, legal, and educational fields. The ethical concerns raised, such as data bias and unclear legal liability, were also significant.

Even though medical students have shown a remarkable amount of interest and have a moderate familiarity with AI, a considerable evidence-based knowledge gap and absence of training persist. These findings emphasize a requirement for curriculum reform that should cover interdisciplinary, ethical AI education to prepare students for working in technology healthcare environments.