The article says clinicians can recognise illness from subtle changes in an 86-year-old patient's breathing, expression and baseline condition that AI systems cannot directly perceive.
It argues AI is useful for pattern recognition, data organisation, diagnostic suggestions and insurance appeals, but evaluates statistical averages rather than the specific person in front of a doctor.
The piece says medicine depends on judging social, emotional and economic factors shaping adherence, decisions and outcomes, making treatment choices too complex to be fully reduced to algorithms.
As AI diagnoses better than doctors in some tests but fails dangerously in others, who should patients and physicians ultimately trust?
With AI set to handle data analysis, how must medical training evolve to cultivate the irreplaceable human skills of the future?
Could AI, trained on biased data, accidentally create a new wave of medical inequality despite its promise of precision healthcare?