Dr. Hilary Lin is a practicing internist whose work spans frontline patient care and the broader question of where medicine is headed.
The question of what artificial intelligence will do to medicine has generated no shortage of predictions, most of them arriving from boardrooms, conference stages, and venture capital decks. Dr. Hilary Lin, an internal medicine physician, offers a view from somewhere closer to the ground, and it is more unsettling, and more hopeful, than most of what gets said in those rooms.
Lin believes the displacement of clinical function by AI is coming, and that it will be substantial. Synthesis, triage, guideline recall, patient navigation, follow-up coordination: she sees much of what currently defines general medicine being absorbed by machine capability over time. But she stops well short of a displacement narrative. Her argument is that the arrival of AI should force medicine to answer a question it has long avoided: what are physicians actually for?
"For a long time, doctors have been trained to be the medical authority. But in many cases, AI will be better at recalling guidelines, digesting massive charts, comparing evidence, and seeing patterns across complex data. We may not always be the smartest entity in the room anymore. But we will still be the only entity in the room that can truly care for the patient."
That reframing carries real weight. Medicine, especially primary care, has spent decades burying its practitioners in documentation, protocol compliance, and administrative overhead, leaving little room for the work that patients most need and that physicians, by training and temperament, are most equipped to provide. Lin's view is that if AI absorbs enough of the machinery, something important could be recovered.
"The clinician's role is not just to produce the right answer. It is to sit with people in fear, help them make hard decisions, understand what matters to them, and guide them through the most vulnerable moments of their lives. If AI can take over more of the machinery of medicine, clinicians may finally have the space to become more human again."
Her sharper concern, though, is about what happens between the technology's arrival and its full potential being realized. The risk, as she sees it, is institutional inertia dressed up as innovation. Healthcare systems operating under existing financial and structural incentives will reach for AI as a way to accelerate the current model, not to question it. Faster throughput, cheaper operations, more scalable care delivery. None of that, Lin argues, gets at what is actually broken.
She is direct about it. "A lot of healthcare innovation is still being designed to sell into incumbents, and incumbents are largely motivated to win at the game of the status quo," she said. The goal, in her view, should be care that is more continuous, more personal, more proactive. Getting there requires a willingness that most large institutions have not demonstrated: to stop optimizing the existing system and accept that the existing system may not be worth preserving in its current form. Whether the industry has the appetite for that kind of rupture remains, for now, an open question.