I find it unlikely that this will happen for roles like doctors and nurses. There are large practical components of training, if they didn’t have the basic knowledge needed it would show through pretty quickly.
Our board exams can only cover so much, so there are little things that can slip under the radar. Like I said in another comment, one of my classmates in medical school used Chat GPT to summarize the reading and it swapped the warning signs for 2 different neurological conditions, one of which is transient and can be fixed with medications, the other is one that can be lethal if not recognized quickly.
Residency training will weed some of them out, but if they never see/recognize those zebras until they show up on the autopsy, that patient still suffered for their laziness and cavalier attitude towards their education.
Doctors spend months or years being supervised. If a doctor cheated on one test then maybe it would slip through, but I see this as no different to just forgetting some part of some learning from years ago, which surely happens.
If a doctor cheated on every exam, their supervisor is going to notice really quickly.
I think we might overestimate how qualified a junior doctor is after doing all the exams. This article (from 2009, well before LLMs) says junior doctors screw up in 8% of prescriptions they write, with half of the mistakes “potentially significant”. This is after any chance at having a supervising doctor review. It says pharmacists generally save the day by spotting the errors.
I also found local numbers showing about 16% of junior doctors never make it through training (the article is saying it’s actually 40%, but 16% is their “normal”). That will include burnout and other reasons for not continuing, but I’m pretty sure with such a decent proportion of people dropping out you can expect the ones that haven’t taken in enough understanding despite passing their exams are commonly dropping out as part of that group, and though LLMs may have increased the pool I doubt we can assume these people make it through training without learning what they need to know. Becoming a doctor is just so intense that it doesn’t seem likely.
As has been pointed out by someone else, our concern should probably lie in those that pass exams then go on to do medical (or other) roles without any supervision period.
Part of my concern is that APPs like nurse practitioners that have no supervised practice as part of their training are going to become even more poorly educated. Their curriculum is already algorithm-based, and because of the Nursing lobby pushing for more and more independence for NP’s, they have dwindling physician oversight requirements (in some places a physician only needs to audit 10% of their notes and never actually lay eyes on the patient themselves.)
As a patient, you do have the right to refuse to be treated by anyone. You may have to wait for a physician to be available, but no one can treat you without your consent and you can always ask for a provider’s title and licensure.
I don’t think I’ve ever been to a Nurse Practitioner without knowing exactly what the outcome would be, and realistically that does take a lot of burden off doctors so long as they correctly recognise what they should and shouldn’t do.
I expect that rules will catch up with the existence of LLMs, the problem is for those few generations that have to live through the transition period…
Ah this is a different risk than I thought was being implied.
This is saying if a doctor relies on AI to assess results, they lose their skill in finding them by themselves.
Honestly this could go either way. Maybe it’s bad, but if machine learning can outperform doctors, then it could just be a “you won’t be carrying a calculator around with you your whole life” type situation.
ETA: there’s a book Noise: A flaw in human judgement, that details how whenever you have human judgement you have a wide range of results for the same thing, and generally this is bad. If machine learning is more consistent, the standard of care is likely to rise on average.
I find it unlikely that this will happen for roles like doctors and nurses. There are large practical components of training, if they didn’t have the basic knowledge needed it would show through pretty quickly.
Our board exams can only cover so much, so there are little things that can slip under the radar. Like I said in another comment, one of my classmates in medical school used Chat GPT to summarize the reading and it swapped the warning signs for 2 different neurological conditions, one of which is transient and can be fixed with medications, the other is one that can be lethal if not recognized quickly.
Residency training will weed some of them out, but if they never see/recognize those zebras until they show up on the autopsy, that patient still suffered for their laziness and cavalier attitude towards their education.
Doctors spend months or years being supervised. If a doctor cheated on one test then maybe it would slip through, but I see this as no different to just forgetting some part of some learning from years ago, which surely happens.
If a doctor cheated on every exam, their supervisor is going to notice really quickly.
But once they get to be supervised, it’s “too late to fail them” (/cynic)
I think we might overestimate how qualified a junior doctor is after doing all the exams. This article (from 2009, well before LLMs) says junior doctors screw up in 8% of prescriptions they write, with half of the mistakes “potentially significant”. This is after any chance at having a supervising doctor review. It says pharmacists generally save the day by spotting the errors.
I also found local numbers showing about 16% of junior doctors never make it through training (the article is saying it’s actually 40%, but 16% is their “normal”). That will include burnout and other reasons for not continuing, but I’m pretty sure with such a decent proportion of people dropping out you can expect the ones that haven’t taken in enough understanding despite passing their exams are commonly dropping out as part of that group, and though LLMs may have increased the pool I doubt we can assume these people make it through training without learning what they need to know. Becoming a doctor is just so intense that it doesn’t seem likely.
As has been pointed out by someone else, our concern should probably lie in those that pass exams then go on to do medical (or other) roles without any supervision period.
Part of my concern is that APPs like nurse practitioners that have no supervised practice as part of their training are going to become even more poorly educated. Their curriculum is already algorithm-based, and because of the Nursing lobby pushing for more and more independence for NP’s, they have dwindling physician oversight requirements (in some places a physician only needs to audit 10% of their notes and never actually lay eyes on the patient themselves.)
These Nurse Practitioners are presumably already required to be highly skilled nurses? Please tell me that’s true 😑
Nope. They can (and these days often do) go straight from their nursing degree to an NP program with no real work experience.
Oh great. Just what I wanted to hear.
As a patient, you do have the right to refuse to be treated by anyone. You may have to wait for a physician to be available, but no one can treat you without your consent and you can always ask for a provider’s title and licensure.
I don’t think I’ve ever been to a Nurse Practitioner without knowing exactly what the outcome would be, and realistically that does take a lot of burden off doctors so long as they correctly recognise what they should and shouldn’t do.
I expect that rules will catch up with the existence of LLMs, the problem is for those few generations that have to live through the transition period…
It already is happening:
https://www.thelancet.com/journals/langas/article/PIIS2468-1253(25)00133-5/abstract
Ah this is a different risk than I thought was being implied.
This is saying if a doctor relies on AI to assess results, they lose their skill in finding them by themselves.
Honestly this could go either way. Maybe it’s bad, but if machine learning can outperform doctors, then it could just be a “you won’t be carrying a calculator around with you your whole life” type situation.
ETA: there’s a book Noise: A flaw in human judgement, that details how whenever you have human judgement you have a wide range of results for the same thing, and generally this is bad. If machine learning is more consistent, the standard of care is likely to rise on average.
Machine Learning is not LLM.
It’s not but the linked paper I responded to doesn’t mention LLMs?
The thread is about ChatGPT, which is an LLM bot, hence the confusion?