Portside

I have a confession: A.I. is making me a better doctor. And I worry that it’s making doctors-in-training worse.

Amid our recent doom cycle about whether A.I. will lead to extreme societal harms, a parallel anxiety has taken hold in medicine about whether A.I. will one day replace physicians. In the context of that panic, I feel a little sheepish admitting that I already use the technology in my practice all the time — especially since I harbor anxieties about what its availability means for my students and residents, and therefore for the profession at large.

This summer, I used an A.I. tool — a platform called OpenEvidence, accessible only to health care providers — to help me choose antibiotics for one patient and to interpret unusual bloodwork for another. A.I. reminded me to consider migraines when a woman presented with dizziness. I chatted with the large language model about treatments for an older man with lung cancer. I have also consulted it about a rash on my father’s back, my son’s fever, a friend’s arm pain and my own difficulty sleeping.

I practice primary care, where every malady is my business. Almost every month, I’m confronted with a complaint or syndrome that I don’t recognize. I’m confident in my mastery over what doctors do — history-taking, reasoning, communicating. I’m less confident about my continued mastery of an ever-evolving universe of facts. Now, the chatbot in my pocket reassures me that I will always know enough, or have access to the cloud-based intelligence that generally does.

All of my students and residents also use OpenEvidence, however, and I worry about the consequences of introducing such a powerful decision aid so early in their careers. Not only have they memorized less than I’d like, but they can seem almost passive in their relationship to their machines.

It’s impractical and counterproductive to train physicians in 2026 without exposure to A.I. Doctoring — as opposed to writing, my other work — is not a creative act that needs to be protected from technological annexation. It’s a service that ought to embrace any resource that improves patient care. Training doctors in the A.I. age, then, means training them to think critically with a machine in the loop, for a speculative future of medicine that we can only glimpse.

I started medical school 20 years ago. Every day since, I have looked something up, skimmed a journal article or talked through a case with a colleague — medicine is a phone-a-friend profession. As a student, I walked around the hospital with “Pocket Medicine,” a standard-issue guide, tucked into my white coat pocket, and I consulted it all day long. I had to understand exactly what I was looking for when I flipped through its pages, and it could not tell me what to do with whatever knowledge I found there.

I haven’t carried “Pocket Medicine” for years. Instead, I am never without my phone. For years, I primarily took my questions to the widely used website UpToDate.com, an evidence-based medical encyclopedia. But now, several times a day, I use OpenEvidence.

OpenEvidence is trained exclusively on peer-reviewed evidence and guidelines, and includes citations for all its claims. Not every insight found there is useful or even accurate, because much of the medical literature it refers to falls short on both those counts. To use the app well, you must stay skeptical as you scroll. It does, however, allow me to trace a statement to a source so I can evaluate it for myself. OpenEvidence reports that over half of American doctors regularly use the app, and it recently announced a plan to expand free access to doctors in developing nations.