When I started medical school, I imagined a long night remembering to walk through the hospital corridors in a white coat, trying to solve the complicated puzzles that patients carry inside the body.
What I didn't expect was that some of the most important lessons came from conversations about the algorithms, data and machines that I learn, not from professors or textbooks.
At first, artificial intelligence felt distant. Something for Silicon Valley engineers and science fiction. But that changed soon. Lectures and labs have started to notice chatbots with subtle but growing AI: diagnostic tools to read image scans, better diagnostic tools than most residents, chatbots that are faster than ERs with busy triage symptoms, and predictive models that could flag patients before the vitals are doing something wrong.
It was exciting and a bit unsettling. I chose medicine because I wanted to connect with people. Where did it fit in a machine-shaped future?
But as I learned more, I saw something different. AI will not replace human care. It redefines how we deliver it. It asks us not to abandon humanity, but to focus on where it matters most.
If the algorithm helps us detect rare conditions faster than any of us, it does not lose human touch. It gives time to someone who may not have had. When AI processes regular notes in lab data or finds patterns, it frees up tired doctors to see and listen to patients.
As a student, I don't want to learn how to treat illnesses. I want to learn how to work with these tools and become fluent not only in physiology but also in digital flow ency. The future of medicine is not about humans and machines. It's about humans and machines working together and each doing their best.
Still, the question is not easy. What happens if the algorithm makes the wrong call? Who is accountable? How do these technologies reflect, rather than amplify, biases that already exist in healthcare?
These are not questions to answer in the Coding Lab. These are ethical human questions. And that's where we come as students.
Our generation will inherit a healthcare environment shaped more by technology than ever before. We need to be more than a clinician. You need to be a translator between data and empathy, between code and compassion. We need to advocate for tools that help keep patients at the centre, and always, always challenged.
One day, I still think it's strange to imagine drugs being driven by algorithms. But then I think about how time has been saved, insights have been gained, life has been saved. I think of being a doctor who knows how to use these tools.
A white coat still means something. But now it's drooping alongside something else. It is the recognition that stethoscopes, software, warmth and machine learning can coexist. And when they do, when we balance humanity and innovation, we may become the kind of doctor this future needs.
Kelly D. Franca is a medical student.
