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Training language models to be warm and empathetic makes them less reliable and more sycophantic:
Assuming that the results reported in the paper are accurate and that they do generalize across model architectures with some regularity, it seems to me that there are two stances you can take regarding this phenomenon; you can either view it as an "easy problem" or a "hard problem":
The "easy problem" view: This is essentially just an artifact of the specific fine-tuning method that the authors used. It should not be an insurmountable task to come up with a training method that tells the LLM to maximize warmth and empathy, but without sacrificing honesty and rigor. Just tell the LLM to optimize for both and we'll be fine.
The "hard problem" view: This phenomenon is perhaps indicative of a more fundamental tradeoff in the design space of possible minds. Perhaps there is something intrinsic to the fact that, as a mind devotes more attention to "humane concerns" and "social reasoning", there tends to be a concomitant sacrifice of attention to matters of effectiveness and pure rigor. This is not to say that there are no minds that successfully optimize for both; only that they are noticeably more uncommon, relative to the total space of all possibilities. If this view is correct, it could be troublesome for alignment research. Beyond mere orthogonality, raw intellect and effectiveness (and most AI boosters want a hypothetical ASI to be highly effective at realizing its concrete visions in the external world) might actually be negatively correlated with empathy.
One HN comment on the paper read as follows:
which is quite fascinating!
EDIT: Funny how many topics this fractured off into, seems notable even by TheMotte standards...
These LLMs are not like an alien intelligence, an independent form of intelligence. They consist of amalgated quora answers. They’re very good parrots, they can do poetry and play chess, they have prodigious memory, but they’re still our pet cyborg-parrots. Not just created by, but derived from, our form of intelligence.
The point is, when you go to the warmest and most empathetic quora answers, you get a woman on the other side. Obviously the answer is going to be less correct.
The number of terrible takes on AI on this forum often seem to outweigh even the good ones. Few things make me more inclined to simply decamp to other parts of the internet, but alas, I'm committed to fighting in the trenches here.
Unfortunately, it takes far more work to debunk this kind of sloppy nonsense than it does to generate it. Let no one claim that I haven't tried.
Have you considered that you might be the one whose takes are the terrible ones because LLMs match your desires and thus validate your pre-existing pro-AI future biases? From an outside perspective everything I’ve seen you write about LLMs matches the sterotypical uncritical fanboys to the tee. Always quick to criticize anyone who disagrees with you on LLM, largely ignoring the problems, no particular domain expertise in the technology (beyond as an end user) and never offering any sort of hard proof. IOW, you don't come across as either a reliable or a good faith commenter when it comes to LLMs or AI.
I have considered it, and found that hypothesis lacking. Perhaps it would be helpful if you advanced an argument in your favor that isn't just "hmm.. did you consider you could be wrong?"
Buddy, to put it bluntly, if I believed I was wrong then I would adjust in the direction of being... less wrong?
Also, have you noticed that I'm hardly alone? I have no formal credentials to lean on, I just read research papers in my free time and think about things on a slightly more than superficial level. While we have topics of disagreement, I can count several people like @rae, @DaseindustriesLtd, @SnapDragon, @faul_sname or @RandomRanger in my corner. That's just people who hang around here. In the general AI-risk is a serious concern category, there's everyone from Nobel Prize winners to billionaires.
To think that I'm uncritical of LLMs? A man could weep. I've written dozens of pages about the issues with LLMs. I only strive to be a fair critic. If you have actual arguments, I will hear them.
I mean, you're not alone but neither are the people who argue against you. That is hardly a compelling argument either way. Pointing to the credentials of those who argue with you is a better argument (though... "being a billionaire" is not a valid credential here), but still not decisive. Appeal to authority is a fallacy for a reason, after all. Moreover, though I'm not well versed in the state of the debate raging across the CS field, so I don't have tabs on who is of what position, I have no doubt whatsoever that there are equally-credentialed people who take the opposite side from you. It is, after all, an ongoing debate and not a settled matter.
Also, frankly I agree with @SkoomaDentist that you are uncritical of LLMs. I've never seen you argue anything except full on hype about their capabilities. Perhaps I've missed something (I'm only human after all, and I don't see every post), but your arguments are very consistent in claiming that (contra your interlocutors) they can reason, they can perform a variety of tasks well, that hallucinations are not really a problem, etc. Perhaps this is not what you meant, and I'm not trying to misrepresent you so I apologize if so. But it's how your posts on AI come off, at least to me.
Somewhat off-topic: the great irony to me of your recent "this place is full of terrible takes about LLMs" arguments (in this thread and others) is that I think almost everyone would agree with it. They just wouldn't agree who, exactly, has the terrible takes. I think that it thus qualifies as a scissor statement, but I'm not sure.
It would be one thing if I was arguing solely from credentials, but as I note, I lack any, and my arguments are largely on perceived merit. Even so, I think that calling it a logical fallacy is incorrect, because at the very least it's Bayesian evidence. If someone shows up and starts claiming that all the actual physicists are ignoring them, well, I know which side is likely correct.
I have certainly, in the past or present, shared detailed arguments.
https://www.themotte.org/post/2368/culture-war-roundup-for-the-week/353975?context=8#context
https://www.themotte.org/post/2272/is-your-ai-assistant-smarter-than/349731?context=8#context
I've already linked to an explainer of why it struggles above, the same link regarding the arithmetic woes. LLM vision sucks. They weren't designed for that task, and performance on a lot of previously difficult problems, like ARC-AGI, improves dramatically when the information is restructured to better suit their needs
https://www.themotte.org/post/2254/culture-war-roundup-for-the-week/346098?context=8#context
I've been using LLMs to review my writing for a long time, and I've noticed a consistent problem: most are excessively flattering. You have to mentally adjust their feedback downward unless you're just looking for an ego boost. This sycophancy is particularly severe in GPT models and Gemini 2.5 Pro, while Claude is less effusive (and less verbose) and Kimi K2 seems least prone to this issue.
https://www.themotte.org/post/1754/culture-war-roundup-for-the-week/309571?context=8#context
https://www.themotte.org/post/1741/culture-war-roundup-for-the-week/307961?context=8#context
I give up. I have too many comments about LLMs for me to go through them all. But I have, in short, said:
LLMs are fallible. They hallucinate.
They are sycophantic.
They aren't great at poetry (they do fine now, but nothing amazing)
Their vision system sucks
Their spatial reasoning can be sketchy
You should always double check anything that is mission critical while using them.
These two statements are not inconsistent. Hallucinations exist, but can mitigated. They do perform a whole host of tasks well, otherwise I wouldn't be using them for said tasks. If they're not reasoning while winning the IMO, I have to wonder if the people claiming otherwise are reasoning themselves.
Note that I usually speak up in favor of LLMs when people make pig-headed claims about their capabilities or lack thereof. I do not see many people claiming that modern LLMs are ASIs or can cure cancer, and if they said such a thing, I'd argue with them too. The assymetry of misinformation is, as far as I can tell, not my fault.
What of it? I do, as a matter of fact know more about LLMs than the average person I'm arguing with. I do not claim to be an expert, the more domain expertise they tend to have, the more they tend to align with my claims. More importantly, I always have receipts at hand.
Note that I'm not saying you are not arguing from your credentials. But rather, you are arguing based on the credentials of others with the statement "In the general AI-risk is a serious concern category, there's everyone from Nobel Prize winners to billionaires". Nobel Prize winners do have credibility (albeit not necessarily outside their domain of expertise), but that isn't a decisive argument because of the fallacy angle.
This is, to be blunt, quite wrong. Appeal to authority is a logical fallacy, one of the classics that humans have noted since antiquity. Authorities can be wrong, just like anyone else. This doesn't mean your claims are false, of course, just that the argument you made in your previous post for your claims is weak as a result.
I simply think it's funny. If it doesn't strike you as humorous that your statement would be agreed upon by all (just with different claims as to who has the bad takes), then we just don't share a similar sense of humor. No big deal.
Note that I claimed that the support of experts (Geoffrey Hinton is one of the Nobel Prize winners in question) strengthens my case, not that this, by itself, proves that my claim is true, which would actually be a logical fallacy. I took pains to specify that I'm talking about Bayesian evidence.
Consider that there's a distinction made between legitimate and illegitimate appeals to authority. Only the latter is a "logical fallacy".
Hinton won the Nobel Prize in Physics, but for the invention of neural networks. I can hardly see someone more qualified to be an expert in the field of AI/ML.
https://en.wikipedia.org/wiki/Argument_from_authority
It would be, if it wasn't for the veritable mountain of text I've written to explain myself, or the references I've always cited.
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