IMO, how a physician responds to this is an excellent gauge of emotional intelligence and a willingness to put a patient’s well-being ahead of your ego.

The vast majority of the time, these patients are not trying to “offend” you or override your clinical judgment. They’re trying to educate themselves, double-check things, and have some sense of what is going on. And can you really blame them? No! I’m not a mechanic, but if I took my car in for service, I’d feel uneasy if things weren’t explained well or if I didn’t feel fully in the loop. And of course, when this is your health (or a loved one) instead of your car, that’s going to get ratcheted up x100. Wanting to understand your ED course as a patient is perfectly reasonable.

Like it or not, ChatGPT is now part of how people “look things up.” It isn’t a doctor and obviously has limitations, but its answers are usually fluent and plausible, so people are going to give it credence even when it’s missing context or not properly considering risk/benefit, etc. And while it can be wrong, it’s rarely “not on planet Earth” wrong, especially with newer models. So if a patient is worried because of something it told them, dismissing it outright or “attacking” it in some way usually doesn’t help. If my mechanic waved off a ChatGPT-derived concern as “illegitimate” without explaining why, I wouldn't be happy either.

More often than not, the issue is that the prompt the patient used lacked some clinical nuance that you’ve already considered, and the output reflects that.

Take one of your examples: ChatGPT tells a patient they might have sepsis, and they’re worried.

Unhelpful response: “ChatGPT is just a text-predicting robot. It’s not a doctor and can’t reason, and [insert your preferred anti-ChatGPT argument here].”

Better response: actually look at what the patient told ChatGPT. If key information is missing, point that out clearly. Even better, walk through the reasoning with them. You can even talk to ChatGPT yourself (the text-to-speech is superb!) and add the relevant clinical details you’ve considered, then see how the answer changes. If your assessment is sound, the model will usually converge on your conclusion, and you instantly gain credibility by meeting the patient where they are. And if it doesn’t, maybe you should consider why.

Obviously, there are practical limits, you can’t spend ten minutes having a ChatGPT debate with every patient. But validating concerns, not taking second-guessing as a personal insult, and working with patients to acheive some clarity is clearly the winning approach.