5 ms·

The problem is that how mistakes are made is crucial. If it's a forced binary choice then sure LLMs can replace humans. But often there are many shades of gre

The problem is that how mistakes are made is crucial. If it's a forced binary choice then sure LLMs can replace humans. But often there are many shades of grey e.g. a human may say I don't know and refer to someone else or do some research. Whereas LLMs today will simply give you a definitive answer even if it doesn't know.

m_ke 2y ago
None of these were binary decisions, but classifying one of around 10-20 conditions or rating cases on a 1-5 scale. In all cases the models trained on a lot of this feedback were more consistent and accurate than individual expert annotators.
- Uehreka 2y ago
  I’m guessing these are also specially trained image classifiers and not LLMs, so people’s intuitions about how LLMs work/fail may not apply.
  - m_ke 2y ago
    It’s the same softmax classifier
- snowwrestler 2y ago
  Wait if experts only agreed 60% on diagnoses, what is the reliable basis for judging LLM accuracy? If experts struggle to agree on the input, how are they confidently ranking the output?
  - petra 2y ago
    You can look at fully diagnosed cases(via surgery for example) and their previous scans.
  - throwup238 2y ago
    Not the OP but the data isn’t randomly selected, it’s usually picked out of a dataset with known clinical outcomes. So for example if it’s a set of images of lungs with potential tumors, the cases come with biopsies which determined whether it was cancerous or just something like scar tissue.
  - Eisenstein 2y ago
    Perhaps they were from cases that had a confirmed diagnosis.
IanCal 2y ago
> Whereas LLMs today will simply give you a definitive answer even if it doesn't know. Have you not seen an LLM say it doesn't know the answer to something? I just asked "How do I enable a scroflpublaflex on a ggh connection?" to O1 pro as it's what I had open. Looking at the internal reasoning it says it doesn't recognise the terms, considers that it might be a joke and then explains that it doesn't know what either of those are. It says maybe they're proprietary, maybe internal things, and explains a general guide to finding out (e.g. check internal docs and release notes, check things are up to date if it's a platform, verify if versions are compatible, look for config files [suggesting a few places those could be stored or names they could have], how to restart services if they're systemctl services, if none of this applies it suggests checking spelling and asks if I can share any documentation. This isn't unique or weird in my experience. Better models tend to be better at saying they don't know.
- ragazzina 2y ago
  You have used funny-sounding terms. Can I ask you to try with: "Is it possible to enable a crolubaflex 2.0 on a ggh connection? Please provide a very short answer." On my (free) plan it gives me a confident negative answer.
  - abecedarius 2y ago
    Claude non-free: > I apologize, but I can't provide an answer as "crolubaflex" and "ggh connection" appear to be non-existent technical terms. Could you clarify what you're trying to connect or enable?
  - IanCal 2y ago
    Sure, I'm interested in where the boundaries are with this. With the requirements for a short answer, the reasoning says it doesn't know what they are so it has to respond cautiously, then says no. Without that requirement it says it doesn't know what they are, and notes that they sound fictional. I'm getting some API errors unfortunately so this testing isn't complete. 4o reliably keeps saying no (which is wrong).
Shorel 2y ago
> But often there are many shades of grey e.g. a human may say I don't know and refer to someone else or do some research. Whereas LLMs today will simply give you a definitive answer even if it doesn't know. To add to the other answers: I know many people who will give definitive answers of things they don't really know. They just rely on the fact you also don't know. In fact, in some social circles, the amount of people who do that, far outnumber the people who don't know and will refer you to someone else.

m_ke 2y ago

None of these were binary decisions, but classifying one of around 10-20 conditions or rating cases on a 1-5 scale. In all cases the models trained on a lot of this feedback were more consistent and accurate than individual expert annotators.

Uehreka 2y ago
I’m guessing these are also specially trained image classifiers and not LLMs, so people’s intuitions about how LLMs work/fail may not apply.
- m_ke 2y ago
  It’s the same softmax classifier
snowwrestler 2y ago
Wait if experts only agreed 60% on diagnoses, what is the reliable basis for judging LLM accuracy? If experts struggle to agree on the input, how are they confidently ranking the output?
- petra 2y ago
  You can look at fully diagnosed cases(via surgery for example) and their previous scans.
- throwup238 2y ago
  Not the OP but the data isn’t randomly selected, it’s usually picked out of a dataset with known clinical outcomes. So for example if it’s a set of images of lungs with potential tumors, the cases come with biopsies which determined whether it was cancerous or just something like scar tissue.
- Eisenstein 2y ago
  Perhaps they were from cases that had a confirmed diagnosis.

IanCal 2y ago

> Whereas LLMs today will simply give you a definitive answer even if it doesn't know. Have you not seen an LLM say it doesn't know the answer to something? I just asked "How do I enable a scroflpublaflex on a ggh connection?" to O1 pro as it's what I had open. Looking at the internal reasoning it says it doesn't recognise the terms, considers that it might be a joke and then explains that it doesn't know what either of those are. It says maybe they're proprietary, maybe internal things, and explains a general guide to finding out (e.g. check internal docs and release notes, check things are up to date if it's a platform, verify if versions are compatible, look for config files [suggesting a few places those could be stored or names they could have], how to restart services if they're systemctl services, if none of this applies it suggests checking spelling and asks if I can share any documentation. This isn't unique or weird in my experience. Better models tend to be better at saying they don't know.

ragazzina 2y ago
You have used funny-sounding terms. Can I ask you to try with: "Is it possible to enable a crolubaflex 2.0 on a ggh connection? Please provide a very short answer." On my (free) plan it gives me a confident negative answer.
- abecedarius 2y ago
  Claude non-free: > I apologize, but I can't provide an answer as "crolubaflex" and "ggh connection" appear to be non-existent technical terms. Could you clarify what you're trying to connect or enable?
- IanCal 2y ago
  Sure, I'm interested in where the boundaries are with this. With the requirements for a short answer, the reasoning says it doesn't know what they are so it has to respond cautiously, then says no. Without that requirement it says it doesn't know what they are, and notes that they sound fictional. I'm getting some API errors unfortunately so this testing isn't complete. 4o reliably keeps saying no (which is wrong).

Shorel 2y ago

> But often there are many shades of grey e.g. a human may say I don't know and refer to someone else or do some research. Whereas LLMs today will simply give you a definitive answer even if it doesn't know. To add to the other answers: I know many people who will give definitive answers of things they don't really know. They just rely on the fact you also don't know. In fact, in some social circles, the amount of people who do that, far outnumber the people who don't know and will refer you to someone else.