Hilary Lin sees the shift coming, and she is not alarmed by it. AI, she says, will take over more and more of what currently defines general medicine: synthesis, triage, coordination, guideline recall, helping patients understand what to do next. The question she keeps returning to is not whether that will happen. It is whether medicine will know what to do with the space that opens up.
"For a long time, doctors have been trained to be the medical authority," Lin writes. "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." What remains, in her view, is something AI cannot replicate: the capacity to sit with a patient in fear, to help someone make a hard decision, to understand what actually matters to them in the most vulnerable moments of their lives. That is not a soft skill or a secondary function. For Lin, it is the whole point.
"If AI can take over more of the machinery of medicine, clinicians may finally have the space to become more human again."
But her optimism is conditional, and the condition is a serious one. Lin's concern is not that AI will harm patients directly. It is that the healthcare system will absorb AI without actually changing, deploying new tools to run broken workflows faster and cheaper, optimizing the current model rather than questioning it. "A lot of healthcare innovation is still being designed to sell into incumbents," she writes, "and incumbents are largely motivated to win at the game of the status quo." In that scenario, AI becomes a performance enhancement for a system that was already failing in fundamental ways.
She is direct about what she thinks the alternative requires. The goal, in her framing, should be care that is more continuous, more personal, more proactive. Getting there means resisting the pull of near-term wins inside the old model. "We have to be willing to break the mold and build a new one." That is a harder sell than efficiency gains, and Lin seems to know it.
What she is describing is less a technology problem than a question of institutional will. The tools, she suggests, may arrive before the willingness to use them differently. Whether medicine treats this moment as an optimization opportunity or a genuine opening for reinvention may turn out to be the most consequential decision the field makes, and it is one that will largely be made by people who are not in the room with patients.
