4 ms·

I don't understand what the aim is here. LLMs have disadvantages compared to human doctors that make them a really, really bad option. 1) they can't take measu

by spwa4 1y ago

I don't understand what the aim is here. LLMs have disadvantages compared to human doctors that make them a really, really bad option. 1) they can't take measurements themselves. 2) they don't adapt on the job. Illnesses do. In other words, if there is a contagious health emergency, an LLM would see the patients ... and ignore the emergency. 3) they are very bad at figuring out if a patient is lying to them (which is a required skill: combined with 2, people would figure out how to get the LLM to prescribe them morfine and ...) 4) they are generally socially problematic. A big part of being a doctor is gently convincing a patient their slightly painful toe does not in fact justify a diagnosis of bone cancer ... WITHOUT doing tests (that would be unethical, as there's zero chance of those tests yielding positive results) 5) they will not adapt to people. LLMs will not adapt, people will. This means patients will exploit LLMs to achieve a whole bunch of aims (like getting drugs, getting days off, getting free hospital stays, ...) and it doesn't matter how good LLMs are. An adaptive system vs a non-adaptive system ... it's a matter of time. 6) they are not themselves patients. This is a fundamental problem: it will be very hard for an LLM to collect new information about "the human condition" and new problems it may generate. There's many examples of this, from patients drinking radium solution (it lights up in the dark, so surely, it must give extra energy, right? Even sexual energy, right?) to rivers or ponds that turn out to have serious diseases lurking around. Meaning a doctor needs to be able to make the decision to go after problems in society when society finds a new, catastrophically dumb, way to hurt itself. Now you might say "but they would still be good in the developing world, wouldn't they?". Yes, but as the tuberculosis vaccine efforts sadly showed: the developing world is developing partially because they invest nothing whatsoever in (poor) people's health. Nothing. Zero. Rien. Which means, making health services cheaper (e.g. providing a cheap tuberculosis vaccine) ... has the problem that it does not increase the value of zero. They won't pay for healthcare ... and they won't pay for cheaper healthcare. And while Bill Gates ad the US government do pay for a bit of this, they're not sustainable solutions. If, however, you train a local with basic medical skills, there's a lot they can do for free, which actually helps.

timschmidt 1y ago
3 and 4 can be highly problematic behaviors in doctors. Patients who have real medical issues are often ignored, scolded, or otherwise denied treatment because of a doctor's perception.
- derbOac 1y ago
  5 is also something that happens sometimes with physicians and healthcare generally anyway, and could be trained in LLMs is my guess. 1 is often (usually?) not done today by physicians per se anyway. 2 is kind of a strawman about LLMs. 6 is maybe the most challenging critique but is also kind of an empirical one, in the sense that if LLMs routinely outperform physicians in decision making (at least under certain circumstances) it will hard to make the case that it matters. I have my biases but in general I think at least in the US there needs to be a serious rethinking about how medical decisions can be made and how care can be provided. I'm skeptical about this paper — the real test will be something like widespread preregistered replication across a wide variety of care settings — but that would happen anyway before it would be adopted. If it works it works and if it doesn't it won't. My guess is under the best of circumstances it won't get rid of humans, it will just change what they're doing and maybe who is doing that.
- spwa4 1y ago
  First you misunderstand, I think, point 3 and 4. The point there is that LLMs are incapable of it (because they don't learn on the job, and that's not the only problem, they also aren't human and thus lack perspective, that hallucination would have catastrophic outcomes here, lack of empathy). But without learning on the job, it simply cannot recognize large scale problems. It's not that they sometimes miss it. We DO NOT know everything, and analyzing wth is happening, including radically changing approach on the job is a necessity, not something optional. Empathy, by the way, is something that happens between 2 people. It is not "inside" one person, and it goes in both directions. So that can't be fixed. Empathy towards you only works if you honestly believe that the other person is genuinely worried about you (and, of course, empowered, able and willing to do something about your situation). If you start out with an LLM, you start out 100% convinced (and correct in that, btw) that they aren't worried about you. So it won't work. That even works in reverse. Patients try to deceive doctors ... but within reason, because there's empathy the other way too. When patients have to deceive LLMs instead for a week off from work, there will be zero empathy, zero shame and zero limitations on behavior that from the patient side. This is not solvable. Hell, it'll be a problem of trust. A doctor is trying to help you ... probably ... with maybe 10% helping the company. An LLM is 100% trying to help the company ... do you take the medicine (or accept nothing's wrong?). Is it what's best for you? Let's face it: the whole point of LLM medicine is that it's not what's best for you. Also ... so your critique is that even doctors sometimes cater to interests that are not the patients' best interest? Ok. True. But you do realize that if you apply that as a critique of LLMs, that are corporate controlled, it's going to be 1000x worse? So I don't understand the critique. Yes doctors aren't perfect, flawed in many ways. That is not a good reason to introduce something 1000x worse. The whole point of LLM medicine is that stealing the profit!
CityOfThrowaway 1y ago
#2 and #3 are both just engineering problems at this point. The foundation models don't adapt quickly, but you can definitely build systems to inject context that changes behaviors And if you build that system intentionally and correctly, then it's handled for all patients. With human doctors, each individual doctor has to be fed context and change their behavior based on the information, which is stochastic to say the least.
howlin 1y ago
A lot of these problems are already managed by nurses or clinic assistants. It's pretty rare to get a lot of face to face time with an actual M.D. Certainly this is true the more you look at poorer communities.
doug_durham 1y ago
They aren't talking about replacing doctors. It's only about LLM's ability to do diagnosis which is a part of being a doctor.
- inopinatus 1y ago
  They chose misleadingly hyperbolic language for their title and abstract. The "discussion" section is then similarly loose with meaning and overwrought claims.
fnordpiglet 1y ago
I feel like this ignores how LLMs work. 1) of course not they would be fed information, but as we build multi modal models that can achieve more and more world integration there’s no reason why not. 2) They’re very adaptive, by their abductive nature they adapt extraordinarily well to new situations. Perhaps too much - hence the challenge with hallucinations. 3) this isn’t necessarily true, as can be seen by some of the modern alignment in SOTA models being more and more difficult to evade. When prompted and aligned with drug seeking behavior training why would you assume they’re bad at detecting this? 4) again I don’t see why this is true. A general purpose LLM might be, but one that’s been aligned properly should do fine. 5) why do you think LLMs are not adaptive? They adapt through reinforcement and alignment. As a larger corpus of interactions are available they adapt and align towards the training goals. There is extensive research and experience in alignment to date, and models are often continuously adapted. You don’t need to retrain the entire base model you can just retrain a LoRA or embeddings. You can even adapt to specific situations by dynamically pulling in a LoRA or embeddings set for situations. 6) They have human like responses to human situations because they’re trained on a corpus of human language. For a highly specialized model you can ensure specific types of human experience and behavior are well represented and reinforced. You can align the behavior to be what you need. All this said I don’t think anyone in this is proposing to take humans entirely out of the loop. But there are many situations where ML models or even heuristics out perform human experts in their own field. There’s no reason to believe LLMs, especially when augmented with diagnostic expert system agents, couldn’t generally out perform a doctor in diagnosis. This doesn’t mean the human doctor is irrelevant but that their skills are enhanced and patient outcomes improve with them help of such systems. Regardless though I feel these criticisms of the approach reflect a naïveté about the ways these models work and what they’re capable of.
- timschmidt 1y ago
  Well said.

by spwa4 1y ago

timschmidt 1y ago

3 and 4 can be highly problematic behaviors in doctors. Patients who have real medical issues are often ignored, scolded, or otherwise denied treatment because of a doctor's perception.

derbOac 1y ago
5 is also something that happens sometimes with physicians and healthcare generally anyway, and could be trained in LLMs is my guess. 1 is often (usually?) not done today by physicians per se anyway. 2 is kind of a strawman about LLMs. 6 is maybe the most challenging critique but is also kind of an empirical one, in the sense that if LLMs routinely outperform physicians in decision making (at least under certain circumstances) it will hard to make the case that it matters. I have my biases but in general I think at least in the US there needs to be a serious rethinking about how medical decisions can be made and how care can be provided. I'm skeptical about this paper — the real test will be something like widespread preregistered replication across a wide variety of care settings — but that would happen anyway before it would be adopted. If it works it works and if it doesn't it won't. My guess is under the best of circumstances it won't get rid of humans, it will just change what they're doing and maybe who is doing that.
spwa4 1y ago
First you misunderstand, I think, point 3 and 4. The point there is that LLMs are incapable of it (because they don't learn on the job, and that's not the only problem, they also aren't human and thus lack perspective, that hallucination would have catastrophic outcomes here, lack of empathy). But without learning on the job, it simply cannot recognize large scale problems. It's not that they sometimes miss it. We DO NOT know everything, and analyzing wth is happening, including radically changing approach on the job is a necessity, not something optional. Empathy, by the way, is something that happens between 2 people. It is not "inside" one person, and it goes in both directions. So that can't be fixed. Empathy towards you only works if you honestly believe that the other person is genuinely worried about you (and, of course, empowered, able and willing to do something about your situation). If you start out with an LLM, you start out 100% convinced (and correct in that, btw) that they aren't worried about you. So it won't work. That even works in reverse. Patients try to deceive doctors ... but within reason, because there's empathy the other way too. When patients have to deceive LLMs instead for a week off from work, there will be zero empathy, zero shame and zero limitations on behavior that from the patient side. This is not solvable. Hell, it'll be a problem of trust. A doctor is trying to help you ... probably ... with maybe 10% helping the company. An LLM is 100% trying to help the company ... do you take the medicine (or accept nothing's wrong?). Is it what's best for you? Let's face it: the whole point of LLM medicine is that it's not what's best for you. Also ... so your critique is that even doctors sometimes cater to interests that are not the patients' best interest? Ok. True. But you do realize that if you apply that as a critique of LLMs, that are corporate controlled, it's going to be 1000x worse? So I don't understand the critique. Yes doctors aren't perfect, flawed in many ways. That is not a good reason to introduce something 1000x worse. The whole point of LLM medicine is that stealing the profit!

CityOfThrowaway 1y ago

#2 and #3 are both just engineering problems at this point. The foundation models don't adapt quickly, but you can definitely build systems to inject context that changes behaviors And if you build that system intentionally and correctly, then it's handled for all patients. With human doctors, each individual doctor has to be fed context and change their behavior based on the information, which is stochastic to say the least.

howlin 1y ago

A lot of these problems are already managed by nurses or clinic assistants. It's pretty rare to get a lot of face to face time with an actual M.D. Certainly this is true the more you look at poorer communities.

doug_durham 1y ago

They aren't talking about replacing doctors. It's only about LLM's ability to do diagnosis which is a part of being a doctor.

inopinatus 1y ago
They chose misleadingly hyperbolic language for their title and abstract. The "discussion" section is then similarly loose with meaning and overwrought claims.

fnordpiglet 1y ago

I feel like this ignores how LLMs work. 1) of course not they would be fed information, but as we build multi modal models that can achieve more and more world integration there’s no reason why not. 2) They’re very adaptive, by their abductive nature they adapt extraordinarily well to new situations. Perhaps too much - hence the challenge with hallucinations. 3) this isn’t necessarily true, as can be seen by some of the modern alignment in SOTA models being more and more difficult to evade. When prompted and aligned with drug seeking behavior training why would you assume they’re bad at detecting this? 4) again I don’t see why this is true. A general purpose LLM might be, but one that’s been aligned properly should do fine. 5) why do you think LLMs are not adaptive? They adapt through reinforcement and alignment. As a larger corpus of interactions are available they adapt and align towards the training goals. There is extensive research and experience in alignment to date, and models are often continuously adapted. You don’t need to retrain the entire base model you can just retrain a LoRA or embeddings. You can even adapt to specific situations by dynamically pulling in a LoRA or embeddings set for situations. 6) They have human like responses to human situations because they’re trained on a corpus of human language. For a highly specialized model you can ensure specific types of human experience and behavior are well represented and reinforced. You can align the behavior to be what you need. All this said I don’t think anyone in this is proposing to take humans entirely out of the loop. But there are many situations where ML models or even heuristics out perform human experts in their own field. There’s no reason to believe LLMs, especially when augmented with diagnostic expert system agents, couldn’t generally out perform a doctor in diagnosis. This doesn’t mean the human doctor is irrelevant but that their skills are enhanced and patient outcomes improve with them help of such systems. Regardless though I feel these criticisms of the approach reflect a naïveté about the ways these models work and what they’re capable of.

timschmidt 1y ago
Well said.