I am a pediatric cardiologist and have cared for children with heart disease for the past three decades. In addition, I have an educational background in business and finance as well as healthcare administration and global health – I gained a Masters Degree in Public Health from UCLA and taught Global Health there after I completed the program.
“Learning never exhausts the mind.”
Leonardo da Vinci
There is an escalation of interest in educating the millions of clinicians as well as leaders in health care on the tenets as well as the promises and limitations of artificial intelligence. This focus on AI has accelerated since the advent of large language models such as ChatGPT. With the availability of AI tools that may not always require programming, the time to learn about AI as a resource is better and perhaps even easier than ever before. For most clinicians, going or returning to school for a formal education in data science and artificial intelligence is not a feasible pathway. The following is an outline of the myriad of stages of healthcare education and training and the possible strategies for education in AI:
Undergraduate Pre-Professional Education
This nascent AI movement in clinical medicine and healthcare for future generations of clinicians will need to have some focus in the early years in colleges and universities. Just as with a foreign language, the earlier these students start in the relevant AI area, the less “accent” or unease they will exhibit later on in their career. They will become “bilingual” in medicine and AI (without an accent) and be the growing valued cohort of dual clinician-data scientists.
- Students, especially those interested in healthcare, can aim to have a strong background in science, technology, engineering, the arts, and mathematics (STEAM) as well as programming
- Students interested in the concepts and applications of AI in healthcare or even just AI can start a club to meet and tp learn about this early in their career
- Students can also join summer internship programs that focus on emerging technologies such as artificial intelligence and extended reality in healthcare
Health Professional Schools
In health professional schools, including medical schools and schools of osteopathic medicine, pharmacy, and nursing, the main challenge of education of AI is the burden of the existing curriculum and the focus on students passing the requisite board examinations. In addition, a topic such AI will need to be introduced without being coupled to computer programming. Lastly, the existing faculty often feels unqualified to discuss AI and other topics.
- AI and other topics can be “embedded” like a motif into the existing curriculum without disrupting the current curriculum and without emphasis on computer programming
- In addition, earlier experience in the clinic or hospital can lead to case and project based learning that will include new technologies such as AI and extended reality
- Engagement and inclusion of the existing faculty in collaboratively teaching the newer topics such as artificial intelligence is essential so no one feels left out or less relevant
Next time, we will discuss education of AI for our postgraduate trainees and clinicians.
The importance of education of our clinicians in artificial intelligence in healthcare will be part of the topics of discussion at the in-person Ai-Med Global Summit 2024 scheduled 29-31 May 2024 in Orlando, Florida. Book your ticket here!