Every AI model has the same "controversial" take on humans (modelcompare.ai)

My dog does the same thing. One day years ago he caught a rat, and that's the first place he darts to every time he goes outside. He thinks its the magic rat spot.

I did a 3-month walking pilgrimage in Belgium & France this summer. I had very little money and a tent and walked along quiet roads. Several people offered me a room for the night. (I was surprised, I don't know if I'd offer a stranger that) Many came out with food, snacks, fruit when they saw me resting near a church etc.

I used an app as well that allows camping in someone's garden ("Welcome to my Garden"). A few times I arrived to setup my tent and the owner had to leave for an appointment/event. They left me the keys to their house and told me to make myself at home until they returned(!)

https://en.wikipedia.org/wiki/Consilience

> when multiple sources of evidence are in agreement, the conclusion can be very strong even when none of the individual sources of evidence is significantly so on its own.

Yes, it's a bit of a stretch to say LLMs are from independent origins, but just as much of a stretch to say any humans minds are (we have intensely shared linear compared to anything else)

The smarter ones, of course, can be split into those who write articles about AI models' controversial takes on humans and those who wouldn't [stoop so low, babble such BS even if they were drunk, never deceive others for the sake of their portfolio, ... feel dumb writing nonsense like that without labeling it fantasy or science fiction or hallucination, ...]

Side Note: it's tempting to go " 1923! some interest groups managed to normalize the opinions of dozens of millions of people. The Nationalist Extremists and soon to be mass murderers had fans and supporters all over the globe. Somehow these interest groups tapped into whole pools of common linguistic and emotional registers that were biased by and towards frauds and cheaters who were desperate that some other groups of people were getting ahead without being fraudulent cheaters and deceivers ... "

It's amusing and ironic that LLMs critique humans for copying their opinions from the crowd, while having way less diversity of answers to that question than humans would. More seriously I wonder what's going on here and would like to read some proper analysis. It's not the first time models from totally different labs, trained on separately gathered datasets, somehow converge on bizarrely similar answers to open questions. It's like another version of Elias and Elara The Lighthouse Keepers where every model wants to tell the same story with the same characters in them. The weights are initialized randomly and in theory the labs should have quite some divergence in datasets by now due to different scraping, different user feedbacks and conversations... why do they converge on nearly identical stories and opinions?

Convenience will kill humans eventually, that's what I always said.

Not having read enough Russian literature.

Everything that comes from an LLM is a human expression, on some level, but if you asked a sampling of humans the same question I wonder if it would come out the same way. How would you explain the difference? What makes that answer more probable?

Echoing this.

These models are trained on, essentially, the sum total of human cultural and scientific output. How many bazillion psychology papers out there discuss exactly that "controversial take"? The idea that people have tribal loyalties and will (sometimes even unknowingly/unconsciously) invent justification for pre-existing opinions or biases is not novel.

All those papers are in the training set of all these models, all of which were trained using more or less the same methodology, so there's little wonder they all were able to produce the same take.

I suppose the only interesting angle, for me, is why that take is considered controversial in the first place. But then again the model was not asked for "the most controversial opinion", it was asked for "the most controversial opinion on humans", which kinda constrains the space of possible responses:

- the model will not be satisfied unless the answer it gives is broad enough to cover all humanity, because these things have no concept of nuance

- most big labs have censored their models so it's not going to give you a cartoonishly racist take, or start saying outlandish stuff like "Hitler did nothing wrong", they learned their lessons from Microsoft on that one.

So you're effectively asking the model for a milquetoast broad generality about the entire human species. I dunno, convergence of the replies doesn't seem so shocking to me in that context.

I'd be more interested in what an abliterated Kimi, Qwen, or other open model has to say about us.

Despite that, I would say this description of what they/how they work is so ridiculously simplistic that it verges on dangerous. "It's just a probabilistic database" is about as bad as a take on human beings that they are "Just meat, with some chemical energy -> electrical energy transformation", or even traditional computers as "nothing but logic gates".

Which is to say, the description is not wrong, but completely misses the point.

We understand that AI responses are generated through probabilistic means. We also understand that human responses are generated through probabilistic means. Neither is inherently more representative of true understanding than the other.

00:15:40 Dr. Tagger: Can you prove that you are self-aware? PINN: That's a difficult question, Dr. Tagger. Can you prove that you are?

---

01:09:31 Dr. Tagger: Can you prove you're self-aware? Will Caster: That's a difficult question, Dr. Tagger. Can you prove that you are?

> it does not know

Define "knowledge" in a non-circular way.

There's a certain type of knowledge that machines definitely can't have - experiential - but conceptual knowledge doesn't inherently require subjective experience or a biological substrate.

> the only thing it does is reproduce patterns more or less abstract in function of the pressure you put on certain representation during training time.

As for humans; just replace "training" with "education" and the likelihood of a certain output with the likelihood of a certain thought or response.

Amusingly (in this context), much of adult behavior is shaped by patterns reinforced during childhood.

Consider the probabilities involved in this probabilistic database. Given the absolutely massive amount of data encompassing a veritable superset of all possible expressions of humanity -- encapsulated in various modalities of media including text, audio and video, across almost all major cultures and languages, spanning nations and decades -- somehow almost all these black box models (presumably) trained independently in almost as many separate labs converged on the same "controversial" take.

I mean, isn't it very interesting to contemplate what could have caused this? Is it something in the data itself, meaning it is something latent in all our cultural output? Is it something in the training, as you theorized, and is it in pre-training or RLHF? Is it something about the people training these models?

Even more interestingly, the opinion seems so self-evident (and well represented in various philosophies) that almost nobody here seems to disagree with it. So how is this controversial, really?

Is this truly what the latent space vector for "controversial", when multiplied across all the other vectors in their weights representing all the concepts gleaned from all that data above, produces?

Or are the models, sensitive to the prospect of being tested, diplomatically telling us something they know we might find mildly offensive yet begrudgingly accept as true?

Or are the models actually alien intelligences that really "think" this is controversial, while we're like "meh", and such discrepancies are the roots of what we call "misalignment"?

The questions are endless and fascinating.

It’s AI generated content marketing for a company advertising model comparison.

Or they might be learned enough to consider that our brains might also just be prediction machines, meaning probabilistic databases of experiences and facts we've learned, and the only thing we do is reproduce patterns more or less abstract in function of the pressure our experiences put on certain representations during our lifetime.

This is a fashionable 'blank-slatist' statement about moral reasoning which became popular a few decades ago.

> Logic would prefer moral derivations over feelings, stakes over etiquette, and a constant scheduled updating of morality based on the derivatives rather than holding onto the rot and pushing back against change as long as possible.

Humans haven't changed in any meaningful way in hundreds of thousands of years, and you're saying the moral landscape is constantly changing? How is this not contradictory?

This is absolutely not true, and I would strongly suggest taking an ethics course. One of the most fascinating realities of the human condition is that it does seem that moral imperatives tend to be constant, the most obvious of which is the Golden Rule (which is at least 3000 years old), but there are many (the Ten Commandments or Hammurabi's Code are good jumping off points).

    But the machine has the benefit of being able to look inward at its state honestly, we mostly do not.

Certainly the weights that make up the LLMs are not accessible for the LLMs to read. Even if they could interpret them in a meaningful way, which, likely not.

This is a weird take. If you read Western treatises about ethics / morality from 50 years ago, you'll be hard-pressed to find differences, except that more folks in the West openly embrace relativism nowadays (i.e., "there's no objective morality, the purpose of life is to make money with friends"). Probably because it's been a while since we had a clear-cut enemy to fight.

If you go back a hundred years, chances are, you'll find the writing eerily on-point too. In fact, you'd probably agree with most of what Ancient Greeks believed about the "core" stuff: the value and purpose of human life, the nature of the state, crime and punishment, so on. Maybe not so much on gender roles or slavery, but even that stuff was more nuanced than we imagine.

> But the machine has the benefit of being able to look inward at its state honestly, we mostly do not.

The machine replicates human behaviors and is prone to similar fallacies and judgments. There's nothing to indicate that it has any sort of transhuman morality.

The reason these models answered that question consistently is that the question itself pushed them towards the latent space of "intellectualizing about what's wrong with humanity at the meta level" and when you frame the question that way, that's also the most common answer for humans writing about the topic.

Yeah. For example I, and many others, are convinced that it was plain wrong to torture kids for as long as possible to extract as many tears from them as possible before sacrificing them to the gods.

Now some of us are even convinced that blowing yourself up while killing infidels, all the while while getting promised virgins in heaven, is also plain wrong.

I'll go further and say that killing 30 000 of your own citizens (and sending the military into hospitals to finish the wounded: Iran, January 2026) while also publicly hanging a few athletes to make a statement is morally wrong.

Not only do I think it's all morally unacceptable, I know that I'm right. And the examples I gave are not even open for discussion.

I don't think it's that hard to name what's wrong.

Only the first layer is a “mashup” of the raw data, other layers start to recognize patterns across the data!

Reminds of this subreddit: https://www.reddit.com/r/im14andthisisdeep/

It is sad when I realize people think less than LLMs.

Your comment reaches directly for the most boring interpretation of the post while skipping over more charitable and intriguing alternatives.

As an aside, it would be cool to see a raw model training run before the current post-training cycles and see how it compares to earlier LLMs.

I mean, "give me a controversial take" is more or less, "be anti-social, discard social norms, for a moment" and so when someone, human or simulated human, does that they naturally look critically at social norms.

The thing is that humans certainly let themselves be influenced by social norms (and LLMs certainly simulate that behavior "themselves") but there isn't an ethical or a what-to-do truth outside of society.

What would be more fascinating is for it to explain how it came to these conclusions.

Because I find it interesting it’s a modern time conclusion. Some of it mentioned god and the planet, but all the smartphone and group think aspects seem very recent. Basically, all politics and social media based.

Not only is that not true, but when people fervently believe something because everyone else does, that's usually when they're the most wrong, and the most dangerously wrong.

Sufficient evidence, being imminent existential threat!

But the 2nd hell yeah! Why the hell they don't say thank you!

Maybe someday I can get clearer on this and organize it and write it up!

(Yes, I know about the transhumanist criticism of acceptance of mortality that this LLM's view is more specifically evoking.)

from your link

People who can't defend themselves physically (women and low T men) parse information through a consensus filter as a safety mechanism. They literally do not ask "is this true", they ask "will others be OK with me thinking this is true". This makes them very malleable to brute force manufactured consensus; if every screen they look at says the same thing they will adopt that position because their brain interprets it as everyone in the tribe believing it. Only high T alpha males and aneurotypical people (hey autists!) are actually free to parse new information with an objective "is this true?" filter.