'Dystopian Levels of Creepy'. Medical Student Perceptions of using Artificial Intelligence and Neurotechnology to Make Summative Assessment Decisions.
<ns3:p>Background Artificial Intelligence (AI) has been increasingly integrated into various sectors of medicine, including medical education. This research examines medical students’ acceptance of the use of AI tools in Observed Structured Clinical Examinations (OSCEs). OSCEs are used globally to evaluate clinical competency but are resource-intensive and subject to examiner bias. AI offers the potential to improve the efficiency and fairness of assessments. However, research on medical student perspectives regarding the integration of AI tools in medical education is limited. Methods This study used a survey tool to assess medical student acceptance of many proposed uses of AI in OSCEs, including as a simulated patient or examiner. Scenarios were presented to students, and their responses were analysed both quantitatively and qualitatively. Results The findings suggest that students have reservations about the role of AI in high-stakes summative assessments but were more accepting of AI in formative OSCEs. Student’s concerns centered on AI’s perceived lack of understanding of human empathy, potential systematic bias, and the trustworthiness of AI models. Conclusions Through critical appraisal of the literature and original results, this research article highlights the need for transparency, education and a hybrid approach that integrates AI into OSCEs with human oversight. By addressing students’ concerns and progressively introducing AI, universities may reduce resistance while yielding AI’s potential benefits. Future research should explore how attitudes of medical students evolve alongside the integration of AI tools in both clinical medicine and medical education.</ns3:p>
Publication Details
- Journal
- MedEdPublish
- Published
- 2026-01-05
- DOI
- https://doi.org/10.12688/mep.21127.1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00