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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.
When someone writes something like that, I can only assume they haven’t touched a LLM apart from chatgpt3.5 back in 2022. Have you not used Gemini 2.5 pro? O3? Claude 4 Opus?
LLMs aren’t artificial super intelligence, sure. They can’t reason very well, they make strange logic errors and assumptions, they have problems with context length even today.
And yet, this single piece of software can write poems, draw pictures, write computer programs, translate documents, provide advice on countless subjects, understand images, videos and audio, roleplay as any character in any scenario. All of this to a good enough degree that millions of people use them every single day, myself included.
I’ve basically stopped directly using Google search and switched to Gemini as the middle man - the search grounding feature is very good, and you can always check its source. For programming, hallucination isn’t an issue when you can couple it with a linter or make it see the output of a program and correct itself. I wouldn’t trust it on its own and you have to know its limitations, but properly supervised, it’s an amazingly capable assistant.
Sure, you can craft a convincing technical argument on how they’re just stochastic parrots, or find well credentialed people saying how they just regurgitate their training data and are theoretically incapable of creating any new output. You can pull a Gary Marcus and come up with new gotchas and make the LLMs say blatant nonsense in response to specific prompts. Eppur si muove.
I am not interested in debating the object level truth of this topic. I have engaged in such debates previously, and I found the arguments others put forward unpersuasive (as, I assume, they found mine). I'm not trying to convince @self_made_human that he's wrong about LLMs, that would be a waste of both our time. I was trying to point out to him that however much he thinks he is critical of LLMs (and to his credit he did provide receipts to back it up), that is not how his posts come off to observers (or at least, not to me).
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