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Comment by openasocket | Hacker News Reader

I find this research odd because I don’t know what field of study to call this. It’s not computer science. It’s almost like behavioral psychology, but for AI agents instead of humans or animals. That said, I feel like these studies lack a lot of rigor. Or maybe it’s a lack of clear direction. Like, what are we trying to determine here? Because these things often involve advanced AI agents and complex harnesses, but then it sounds like they are given a very minimal prompt. What are we really studying then? Would the outcome be completely different with a different prompt? Can we generalize these results to other models? Different generations of models, different levels of thinking? What if we tried fine-tuning the model to this scenario? Is this fundamentally how any LLM would act, or is this some artifact of our current, generalized fine-tuning?

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Reads to me like Proto-psycho-history. Attempting to model behavior mathematically, with the assumption that all human behavior can be modeled this way, and that these models can be useful for predicting human behavior.

Saw an article a quarter century ago in The Atlantic about simple population models as a way to explain more complex behavior. One was: randomly distribute blue and red cells across a 2D grid. Every frame, pick a random cell: if it has at least one color like it nearby, leave it. If not, move it to a random location. Over many generations, segregated color formed. The article used this to describe something about segregated communities forming. I offer no opinion about the credibility of the article, but it was fascinating to me as a baby nerd, and seems at least a little related to this article’s line of thinking.

Once you understand how complex the human brain is, with 86 billion neurons and 100 trillion synapses, formed over billions of years of evolution, comparing that to the machines we have built makes them seem silly and extremely simple in comparison.

Psycho-history is fiction. You're not going to be able to model a single human much less millions of humans and their environments.

Elementary Wizardry: Summoning and Management of Elementals and Golems

I think this is mostly just software benchmarking. The most science that can probably be extracted from this case study is probably a couple data points on where we are and where we can improve with AI agents. It seems like a decent task to optimize for. It might also work as a proof of concept for an economics study or theoretical political science.

I think large LLMs can be seen as a representation of humanity's collective thought processes... almost as if humanity were a single entity.

They have read pretty much everything we have ever written, good and bad, so they're kind of a mirror of us, as a species. Not a perfect one, but still.

Aliens could probably use a llm to get a crash course on what humans are actually like, and how to interact with them.

They are the collection of all human thought processes, as curated by Definitely Not Evil Corporation.

Asimov predicted "Robopsychology".

> I find this research odd because I don’t know what field of study to call this.

Probably multiple with very complex system dynamics, feedback loops: Cliodynamics, Cultural evolution, Cultural anthropology, Archaeology, Sociology Political science, Institutional economics, Urban planning, Complexity science, Social ecology

I suggest thinking of it as psychology on a mathematical model of collective human works, and I’m currently curious to see the differences of models trained only on specific cultures

Computational sociology? I imagine a model of society could come out of this, then you could create hypothetical societies and see how they behave.

Sociology is the right concept. It sits somewhere between system analysis and emergent human "sort of" sciences, like economics and sociology, where we can detect structures but humans are too complex to surface any platonic concepts with much confidence.

AI interaction may give us a cleaner way to test and analyze emergent properties that sit beneath so of the softer sciences, giving us a harder science that we had no way to investigate before.

Computers science is just applied math, has nothing to do with the machine.

The term computer was coined to describe humans engaged in applied math jobs before the machines existed.

The models are matrices of values engaged in reducing options to the most desired outcome given inputs. That's software dev.

"Fundamentally" or "fine tune" is meaningless; no model spontaneously emerged through a membrane from another reality. They’re all fine tuned from nothing into a model or from a general model to a specialized one.

You're circumlocuting semantics to say something for social media, but the physical provenance is clear. They're not of mythical origin and it's still math relative to set of memory values.

Machine psychology

Well, obviously Psychology + (computer) science = Scientology

It’s the same way psychology works on humans. Black box observational stuff.

You can’t generalize anything here because the psychology of the model can be affected by system prompt, reinforcement training, and training data. What you observe here can be wildly different if you change any of the underlying things I mentioned.

It’s like watching an ant colony.

it’s just machine learning but instead of doing things the old fashioned way everyone just uses llms now. this is nothing new

Never trust an experiment you haven't faked yourself.

I'm not sure it's that serious, but they did have two models, Claude and gpt were on opposing teams.

The label might come later, but cooperative or adverserial behavioral patterns matter deeply when deploying agents to act as weapons of defense or business builders.

>I find this research odd because I don’t know what field of study to call this.

AI bullshit hype generation.

Call it what it is: slop.

It has zero intrinsic value beyond the headline. The whole goal is to market LLMs if the result is successful.

you can’t see any benefits to studying how LLMs behave in long horizon multi agent tasks?

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