AI, a promising tool in augmenting medical education 

This article was exclusively written for The European Sting by Ms. Lantum Lydia Dzeenyuy, a 21 year old third-year medical student in the faculty of Health Sciences University of Buea, Cameroon. She is affiliated with the International Federation of Medical Students Associations (IFMSA), cordial partner of The Sting. The opinions expressed in this piece belong strictly to the writer and do not necessarily reflect IFMSA’s view on the topic, nor The European Sting’s one.

Artificial intelligence (AI) is a scientific discipline focused on understanding and creating computer software that mimics and extends human rational thinking and actions[1]. The use of AI in different fields of education is fast growing; this is due to some advances in AI such as machine learning, deep learning, natural language processing, speech recognition, decision management, virtual agents, and robotics. 

However, the use of AI as a tool to augment medical education is a cause of great controversy and concern, with one of the primary reasons being a lack of literacy about its application in medical education [2]. Adding AI education into the medical curriculum to increase literacy is a big problem because the curriculum is already very intense and bulky resulting in a lack of courses that educate medical students on the uses, challenges, as well as some skills necessary to benefit from Its use.

Medical education today entails memorising large volumes of information and its application in patient care to pass medical exams, as well as building good communication skills, empathy, and interpersonal skills, which are invaluable in medical practice. 

Some useful applications of AI in medical education that would go a long way in lessening the burden on learning include [3,4]:

1. Objective assessment and feedback on learning:  this is brought about by generative AI, which uses existing digital content like texts, videos, images, and audio to provide accurate feedback on learning and assessment based on the learner’s performance. 

2. Adaptive learning: AI can be used to adjust teaching methods based on student’s performance and progress, as well as map out personalised learning pathways to meet the student’s needs
3. Make learning more interactive: AI does this by generating simulations of surgical procedures, which allows trainees to practise in a controlled environment and have a better understanding of the task involved. AI also generates images that make learning less abstract and interesting.
4. Facilitates Research: AI assists in making literature reviews and summaries, giving medical personnel access to up-to-date information 
5. Facilitate decision-making: AI puts together large amounts of useful information that can help physicians make informed choices about diagnoses and treatment.
6. Facilitate Data Management: AI can generate Electronic Health Records (EHR) from medical records, pharmacy notes, paraclinical findings, and environmental data, process this data, analyse it, and make helpful recommendations to medical personnel using machine learning.

Many challenges come with the use and implementation of AI in medical education; some include[2]

• Concerns about accuracy and efficacy because AI has been known to provide false references and biassed data. 
• A lack of human interaction is associated with the use of AI, as good communication skills and empathy are crucial in healthcare.
• An over-dependence on AI which, in the long run, severely affects critical thinking and the potential for good decision making.

Finally, associated with the use of AI is the fact that its algorithm of providing information and feedback is obscure, making it a black box, which is dangerous for healthcare as adverse effects could be unpredictable.

 AI is predicted to grow exponentially as technology develops and with the potential to transform medical education in the future. Thus, AI literacy and government policy that regulate the use of AI as a tool to augment medical education will allow physicians to concentrate more on building good communication skills and empathy and make informed decisions concerning patient care.

References

1.  Ken M. Artificial intelligence in medical education. Medical Teacher 2019.  DOI: 10.1080/0142159X.2019.1595557
2. Ketan P, Michiel S, Rishi N, Josip C,  Prabath N.Introducing Artificial Intelligence Training in Medical Education. JMIR Med Educ. 2019;5(2):e16048 doi:10.2196/16048
3. Carl P, Christian R. Opportunities, Challenges, and Future Directions of Generative Artificial Intelligence in Medical Education: Scoping Review. JMIR Med Educ. 2023;9:e48785

doi:10.2196/48785

4. Baidoo-Anu D, Owusu A. Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning.Journal of AI 2023; 7(1): 52-62.

About the author

Lantum Lydia Dzeenyuy is a 21 year old third-year medical student in the faculty of Health Sciences University of Buea, Cameroon. She is a Cameroonian, an anglophone, and is currently internally displaced due to the anglophone crisis in her country. She aspires to not only be a medical doctor but to be a scientific researcher one day. She’s not a great fan of sports but greatly enjoys rollerblade skating. She loves reading books, especially classic novels, enjoys concepts of philosophy and debate, and is an advocate for gender equality. 

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