This doesn't surprise me. When I see a doctor in real life, they are moving patient to patient quickly and are always behind schedule. I'm sure they are also losing lots of time to submitting notes and administrative things. So they don't really have time to deeply analyze my health situation. Multiple times I've been the one to compare different test results, establish patterns or correlations, perform research, and suggest possible diagnoses or solutions to my doctor, who then double-checks my work and accepts my theory or offers an alternative. This collaborative approach has been helpful because there are many conditions where you could mistakenly match symptoms to some generic condition if you don't look at things more deeply. After all, there is a very broad set of medical conditions out there and a single doctor cannot reasonably be expected to know all of them deeply.

But I've also had medical professionals, particularly the non doctors (nurse practitioners, physicians assistants, etc) who are much less receptive and more fixated on their first guess, which has sometimes resulted in precious lost time and repeated visits for me. The linked research finding is interesting, and I think highlights the pitfall of professionals who believe too much in their own expertise or gut feeling even when they've not really examined the case carefully:

> The chatbot, from the company OpenAI, scored an average of 90 percent when diagnosing a medical condition from a case report and explaining its reasoning. Doctors randomly assigned to use the chatbot got an average score of 76 percent. Those randomly assigned not to use it had an average score of 74 percent.

> The study showed more than just the chatbot’s superior performance.

> It unveiled doctors’ sometimes unwavering belief in a diagnosis they made, even when a chatbot potentially suggests a better one.

> And the study illustrated that while doctors are being exposed to the tools of artificial intelligence for their work, few know how to exploit the abilities of chatbots. As a result, they failed to take advantage of A.I. systems’ ability to solve complex diagnostic problems and offer explanations for their diagnoses.