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Culture War Roundup for the week of August 11, 2025

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Training language models to be warm and empathetic makes them less reliable and more sycophantic:

Artificial intelligence (AI) developers are increasingly building language models with warm and empathetic personas that millions of people now use for advice, therapy, and companionship. Here, we show how this creates a significant trade-off: optimizing language models for warmth undermines their reliability, especially when users express vulnerability. We conducted controlled experiments on five language models of varying sizes and architectures, training them to produce warmer, more empathetic responses, then evaluating them on safety-critical tasks. Warm models showed substantially higher error rates (+10 to +30 percentage points) than their original counterparts, promoting conspiracy theories, providing incorrect factual information, and offering problematic medical advice. They were also significantly more likely to validate incorrect user beliefs, particularly when user messages expressed sadness. Importantly, these effects were consistent across different model architectures, and occurred despite preserved performance on standard benchmarks, revealing systematic risks that current evaluation practices may fail to detect. As human-like AI systems are deployed at an unprecedented scale, our findings indicate a need to rethink how we develop and oversee these systems that are reshaping human relationships and social interaction.

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:

A few months ago I asked GPT for a prompt to make it more truthful and logical. The prompt it came up with included the clause "never use friendly or encouraging language"

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.

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 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.

I don’t care enough to get into a 50-page yudkowski talmud brain debate on the theory, I admit it. But my explanation of this particular quirk has an elegant simplicity that smells of truth, in my opinion. AI enthusiasts here think they’re talking to a novel, alien intelligence. The one-shotted normies are not that different, they think they’re talking to god. I think they’re talking to Karen.

Does your theory need to change if I can demonstrate LLMs solving questions that were not previously on Quora, or otherwise on the internet? I'll admit it solved that particular problem poorly, but it seems a pretty critical issue for any parrot-style claims.

Nah, I don’t think it has solved anything in a truly novel way. I’ll just stay a sceptic until the evidence gets stronger, incontrovertible. I don’t want to turn into one of those AI fiends, hanging onto a new AI’s every burp, feverishly fantasizing about utopia one day, extinction the next.