Bringing AI into the classroom

Drawing on her background in computer science, Zia recently led a research project examing how AI is being introduced into the curricula of undergraduate health sciences programs across Canada and the United States.

She presented her findings at the 2025 International Congress on Academic Medicine and at a conference hosted by the College of Medicine in June.

We reached out to Zia to learn more about her background, her research interests and how her work with AI is already making an impact in the college's undergraduate medical curriculum.

I completed a BSc in computer science at the University of Regina prior to being accepted into the College of Medicine. During my undergraduate studies, I received an Natural Sciences and Engineering Research Council of Canada (NSERC) Undergraduate Student Research Award grant to explore the applications of using machine learning to forecast populations within Saskatchewan.

I continued to pursue this interest during medical school as president of the USask Artificial Intelligence in Medicine Students Society (AIMSS), leading research projects across a variety of AI applications in medicine, from curriculum to preventing physician burnout.

During my undergraduate degree, I had a great professor who taught me some of the basic concepts of coding and happened to complete research in machine learning and AI. Artificial intelligence seemed very futuristic to me at the time and so I was very excited for the opportunity to contribute! I enjoyed getting to see some of the work that goes into developing machine learning algorithms and the data required for it.

As I entered medical school, I recognized the value that AI could bring to the field of medicine. I searched for ways that I could combine both the computer science chapter of my life that I was leaving behind and the medicine chapter of my life that I was just starting.

I met with Dr. Scott Adams (MD, PhD) during the second semester of my first year of med school, after hearing about some of the work that he was doing in the field of artificial intelligence with medicine. We discussed ideas for research projects, and what really guided the conversation was that I still wasn’t sure what specialty I was interested in. I wanted to keep my research relatively broad so that it could be applied to any field that I pursued.

At the same time, Dr. Adams had started co-leading the USask AI Working Group, which he suggested I join to provide a student voice. A topic that was brought up in our meetings was the importance of medical students – like students in any field – learning about the applications of AI and the considerations involved in its use. However, as AI is a new and constantly changing topic, it was difficult to prioritize what to include in the curriculum. 

As a result, we decided that my research project would explore what other institutions teaching students in health professions are including in their curricula. The goal was to see if there are any common themes that could inform not only our curriculum but also those at other institutions.

My research has already informed the curriculum by adding four hours of AI teaching in pre-clerkship, which will be implemented starting in the 2025/2026 school year. Based on the preliminary data from my survey, we prioritized certain topics – such as ethical and legal implications of using AI – along with providing students with guided opportunities to use AI, helping them feel more comfortable with it as they transition to clinical practice. This was done to allow students to use AI in a deliberate and informed manner that aligns with their responsibilities as health care providers. This approach reflects what we saw taught in health care curricula across the schools we consulted.

We believe that starting early is better for students, so they have the skills they need to use AI effectively before they are exposed to it. However, we realize that students are at different stages, and people who are in clerkship, residency, and practice may not have developed those skills. So, there is definitely a role for providing AI teaching at every step of one’s career.

Having discussions around the acceptable use of AI is incredibly important to provide guidance to people who want to incorporate AI into their teaching, and these discussions need to be ongoing as technology constantly evolves. Being open-minded about the benefits of AI is also essential. Though it is tempting to ban its use outright, people will encounter AI regardless, and it is better to become proficient in using it. Having a list of AI models vetted by USask, so that educators know they can trust the data being used, is also beneficial.

I had the opportunity to present a workshop at the Research, Innovation, and Scholarship in Education (RISE) faculty development conference this past June, where I discussed principles for incorporating AI into teaching, along with providing time for practicing using those skills and asking questions that come to mind when learning about those principles.

There were no obvious differences across the health professions in their approach to AI education from my preliminary look at the data. The same topics are important across the health care fields of ethics and applications in clinical practice, and the way we teach our students using a mix of lectures and small group discussions is also very similar. This makes sense to me, as we all work together as different parts of the same team to achieve the same end goal of patient care. Therefore, it would make sense that what we value regarding AI use is very similar as well!

I loved this research and the opportunities that came with it. Most memorably, presenting my research at International Congress on Academic Medicine (ICAM) to a packed room of people all interested in learning about AI in medicine really encouraged me, as it showed that my work was not only valuable to the University of Saskatchewan but also across Canada. I am hoping to inspire other institutions to also add AI teaching into their health care profession curriculum.

Aside from the applications of AI in education, I also am exploring how AI can help prevent physician burnout – particularly by reducing administrative burden through AI scribes and by using AI with image recognition to help reduce the number of unnecessary referrals that specialists receive for benign conditions. With every project that I complete, I wonder about other ways to incorporate AI, and I am sure that I will not run out of ideas to explore with research within the constantly changing field of AI!