Doctors and AI

 Danielle Ofri, NY Times -   Like most doctors these days, I’ve been incorporating medical artificial intelligence tools into my practice. It’s become so easy to type in a quick description of an 86-year-old male with heart failure, diabetes and gout — toss in some test results, and see what the bot spits out. I appreciate that A.I. can expeditiously outline next steps for the clinical evaluation, or provide suggestions for rarer diagnoses or spit out a feisty appeal letter for an insurance denial. But the problem is that A.I. is evaluating only some statistical average of 86-year-old males with heart failure, diabetes and gout. It is not assessing that one specific 86-year-old man with these conditions whom I am looking at across the waiting room.

There’s an ocean of distance between the “patient” that A.I. is analyzing and the patient that the human doctor or nurse is assessing. Navigating the gap is something writers also grapple with. When making a diagnosis, as it were, of good writing to publish in the literary journal I edit, I look for characters that are fully realized, with physicality that is palpable and an emotional complexity both visceral and vivid. These details aren’t always made explicit, but pieced together in hints and subtle cues. What I’ve realized over the years is this is not so different from what a doctor has to do when assessing her patient’s health.

This is the inherent limitation of A.I. in medicine. It’s simply impossible — at least for now — for these tools to truly see the multidimensional patient. A.I. can’t know how the agony of a child estranged by substance use affects the blood pressure. It can’t factor in the economic and social crosscurrents that bear on medication adherence. It can’t account for the simmering grief of a lost spouse that influences a patient’s health decisions far more than any clinical guideline.