Academic Journal
Exploring Artificial Intelligence in the Nigerian Medical Educational Space: An Online Cross‑sectional Study of Perceptions, Risks and Benefits among Students and Lecturers from Ten Universities.
| Title: | Exploring Artificial Intelligence in the Nigerian Medical Educational Space: An Online Cross‑sectional Study of Perceptions, Risks and Benefits among Students and Lecturers from Ten Universities. |
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| Authors: | Oluwadiya, Kehinde Sunday, Adeoti, Adekunle Olatayo, Agodirin, Sulaiman Olayide, Nottidge, Timothy Eyo, Usman, Mustapha Ibrahim, Gali, Mtaku Bata, Onyemaechi, Ndubuisi Onu, Ramat, Ali Mohammed, Adedire, Adejare, Zakari, Lawal Ya’u |
| Source: | Nigerian Postgraduate Medical Journal; Oct-Dec2023, Vol. 30 Issue 4, p285-292, 8p |
| Abstract: | Background: The impact of artificial intelligence (AI) has been compared to that of the Internet and printing, evoking both apprehension and anticipation in an uncertain world. Objective: This study aimed to explore the perceptions of medical students and faculty members from ten universities across Nigeria regarding AI. Methods: Using Google Forms and WhatsApp, a cross-sectional online survey was administered to clinical year medical students and their lecturers from ten medical schools representing all the six geopolitical zones of Nigeria. Results: The survey received 1003 responses, of which 708 (70.7%) were from students and 294 (29.3%) were from lecturers. Both groups displayed an average level of knowledge, with students (Median:4, range −5 to 12) significantly outperforming lecturers (Median:3, range −5 to 15). Social media (61.2%) was the most common form of first contact with AI. Participants demonstrated a favourable attitude towards AI, with a median score of 6.8 out of 10. Grammar checkers (62.3%) were the most commonly reported AI tool used, while ChatGPT (43.6%) was the most frequently mentioned dedicated AI tool. Students were significantly more likely than lecturers to have used AI tools in the past but <5% of both groups had received prior AI training. Excitement about the potential of AI slightly outweighed concerns regarding future risks. A significantly higher proportion of students compared to lecturers believed that AI could dehumanise health care (70.6% vs. 60.8%), render physicians redundant (57.6% vs. 34.7%), diminish physicians’ skills(79.3% vs. 71.3%) and ultimately harm patients(28.6% vs. 20.6%). Conclusion: The simultaneous fascination and apprehension with AI observed among both lecturers and students in our study mirrors the global trend. This finding was particularly evident in students who, despite possessing greater knowledge of AI compared to their lecturers, did not exhibit a corresponding reduction in their fear of AI. [ABSTRACT FROM AUTHOR] |
| Subject Terms: | ARTIFICIAL intelligence in medicine, MEDICAL students, DIGITAL technology, CHATGPT, SOCIAL media, CROSS-sectional method |
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| ISSN: | 11171936 |
| DOI: | 10.4103/npmj.npmj_186_23 |
| Database: | Complementary Index |
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