LLMorphism: When humans come to see themselves as language models

Den_VR

> are [we] beginning to attribute too little mind to humans. I don’t think this way of thinking started with LLM. Does Systems Based Thinking also attribute too little mind to humans?

TMWNN

Highly relevant: Reading Doesn't Fill a Database, It Trains Your Internal LLM < https://tidbits.com/2026/02/28/reading-doesnt-fill-a-databas... >

stavros

I'm sure we don't know for sure that humans work like LLMs, but do we know that they don't ?

artninja1988

I think it's meaningless anyway. A calculator doesn't multiply numbers like a human does. The important part is to develop systems that can do many human tasks

Alifatisk

> When artificial systems produce human-like language, people may draw a reverse inference: if LLMs can speak like humans, perhaps humans think like LLMs. I think I experienced this when I learned about LLMs, chain of thought, thinking tokens, short-term memory context, and long-term memory context. I began applying these concepts to real life and reasoning about how our brains work as if these concepts described how our brains actually function. But maybe this is more akin to the Tetris effect?

dr_dshiv

I teach students to use their own imagination like generative AI. Prompting works. They just need a bit of practice.

thepasch

This paper introduces a term and instantly defines it as a definitely biased thing that is definitely happening, then spends its entirety arguing against the strawman it built itself. Not a single sentence is spent actually arguing with the idea or any of its points (other than the “partial similarities” paragraph on page I just realized the pages aren’t even numbered). In general, the terms “LLM-like” and “human-like” are used all over the place, and in contrast with each other, but they’re never actually defined . It all just seems more vibes-based than anything else. And “treating the human cognitive process like it’s similar to the LLM cognitive process might lead to a society where epistemics turns into a discipline where plausibility is an acceptable substitute for empiricism” has got to be one of the most ridiculous notions I’ve ever read in a paper (ctrl+F “fifth pathway is epistemic” for the exact quote).

MichaelRo

Nothing new under the sun. When clocks and precision mechanics started in the 17th century, there was a tendency to view humans as "machines". Computers came, suddenly human brains are "computers". Now we're LLMs. If scientists make green jelly that emits thoughtful judgements, humans will be compared to green jelly.

vachina

I mimic how LLM responds when I talk to my boss lol. Appear useful and present verbose facts. Works pretty well so far.

fhars

Before electric computers, the human mind was a steam engine: https://www.ezrabrand.com/p/releasing-the-pressure-a-dive-in...

Der_Einzige

No template. No figures. No attempt. This shouldn't be on Arxiv. Vixra was created for such low effort content.

j16sdiz

I looked up other paper from the same author. Looks like he mostly publish something about "social behavior". This "paper", IMO, is just saying "Hey, I notice this is happening. This is why it could be interesting for social science researchers" with without any real research or result.

ineedasername

The author lightly touches on other ways humans have viewed cognition, “computationalism” as one, but somewhat brushes these aside as though LLMs are somehow a unique expression of this tendency. That seems unlikely to me but we’re pretty early days into the tech to start assuming and concluding every initial hot take on “AI is Doing $Thing”. Especially when this particular thing is just one in a very long line of metaphors humans make to our own minds’ operations every time a new major technology comes to play a pervasive role in society. Computers, steam engines, even aqueducts were not immune to comparisons of thought flowing like water, funneled by deliberate intent, etc. And for some, a certain amount of hand wringing worry or even moral panic about “what it’s doing to us”, eg taking away critical thinking because “OMG calculators!”

bluejay2387

A more insidious related pathology- marital induced projected LLMorphism... where your wife constantly accuses you of having the personality of a large language model.

daishi55

I certainly analogize my behaviors to LLMs. How I learn, how I think - I see it reflected in the LLMs I use every day.

HarHarVeryFunny

Don't be too hard on yourself. If you've never walked to the car wash, then you are probably not an LLM. Here's the thing though, unlike the old brain=computer analogy, this one may actually have a little truth to it. Not that your whole brain is an LLM, or even that the language part of your brain is just an LLM, but the language part may indeed be functioning in a similar way to an LLM to extent that it: - Uses a hierarchy (cortical patch-panel) of parallel processing steps - Is prediction based - Is largely (but not 100%) auto-regressive - Isn't actually specialized for language The same is going to be true for all of our cortical areas/functions. The cortex is pretty much the same everywhere (it's 6 layers of neurons with a specific layer-to-layer interconnect pattern), and is therefore going to work the same everywhere. What your cortex has that an LLM doesn't, and therefore makes your language cortex much more capable than an LLM, is that it learns incrementally and continually, based on prediction failure. An LLM/Transformer also learns from prediction failure, but needs the LLMs whole "life history" (training set) to be present at the same time, presented over and over, and learns via a special training algorithm. Your cortex in contrast doesn't have any magical external trainer, so has to learn for itself, and might be considered as 1/2 inference network and 1/2 prediction feedback/learning network. The other major difference between an LLM and your language cortex is that the LLM is 100% auto-regressive, while your language cortex also has external inputs that bias/control generation, so that you can talk about things you are experiencing and what is going on in your head, not just generate a self-predicting sequence of words.

tedbradley

> "LLMorphism may encourage objectification when people are seen as replaceable mechanisms or output-generating systems. However, LLMorphism does not necessarily involve using another person instrumentally. Its primary content is representational: it concerns how humans are conceptualized, not necessarily how they are exploited ." This is quite a scary truth. A year or two ago, I saw a person with a job where he wrote small articles for a website. The boss contacted him, asking if he wanted to become an AI-assisted writer instead for less money . "No," he said, wanting the full payments for his writing prowess. A week or two later, they canned him, and the website's articles nosedived in quality. LLMs expand the supply of "competent" labor. After mass firings, the remaining workers, desperate for income, accept lower wages for AI-assisted roles. Wealth consolidates upward while wages race downward. So I think LLMorphism might tie closely to exploitation. Mass firings and lower salaries going around while the 0.01% of machine-learning companies consolidate wealth by servicing numerous roles autonomously in some cases and by reducing salaries due to the larger body of "qualified" workers who can technically finish the job despite not having qualified in the past. > " LLMorphism is also distinct from predictive processing and related Bayesian theories of cognition. Predictive processing holds that the brain continuously generates predictions about sensory input and updates internal models in light of prediction error (Clark, 2013; Friston, 2010; Hohwy, 2013). But predictive processing does not imply that humans are LLM-like, nor that human understanding is merely text generation. Indeed, many predictive-processing accounts are deeply embodied and action-oriented (Allen & Friston, 2018; Clark, 2015; Pezzulo et al., 2024). " I agree wholeheartedly here, because neural networks (NN) are stateless functions usually (not stuff like recurrent ones). On the one hand, with an infinitely fast computer, you retrieve the answer instantly. Brains, on the other hand, have neurons that communicate with signal delay. I bet if, in a weird world, we could simulate a brain with zero delay, a mind would cease to function correctly. Plus, neurons accumulate charge steadily before firing to nearby neurons. With NNs, you simply add up all the numbers, the "charge," and the ReLU function (or sigmoid for old-school machine-learning researchers) instantly "simulate" a neuron firing off to neurons connected to it. > " and and " Just a heads up, you have a typo here. > " LLMorphism may therefore make fluency appear sufficient for understanding and, in doing so, devalue expertise and weaken educational norms. " I have heard the horror stories that youngsters these days are attached to screens with less ability to focus, but I'm not scared of that claim yet . For every generation, there have been those who kick the can down the road, skirting responsibilities, and all that changes with the generation is the activity: Instead of kicking a can down the road, they slide their finger across their phone's screen. The real test is tracking how many students across HS are in AP courses, learning Newtonian mechanics, electromagnetism, and of course, calculus among a couple others. Is that number dropping relative to the 90s and the aughts? Is it roughly the same as a percent of students? Or is it even going up, perhaps LLMs helping some types of learners explore topics to help them qualify for AP coursework? Now, if the percent is nosediving, then* I will be terrified for what the future holds for them and for me. > " clinicians also rely on how patients appear. Research on clinical communication shows that nonverbal behaviour is central to physician–patient interaction, including the expression of emotion, empathy, distress, and relational understanding " LLMs are becoming multimodal with pictures "understood." No reason LLMs won't catch these non-verbal signals in the future that I can think up. > " The risk may be particularly acute in mental health, where suffering can be difficult to articulate and where coherent self-description does not always track clinical severity; behavioral and nonverbal signs such as psychomotor retardation, agitation, facial expression, vocal dynamics, and posture can provide clinically relevant information beyond verbal report (Dibeklioğlu et al., 2015) " This is a great point, because a lot of people with schizophrenia and bipolar disorder with psychotic features suffer from anosognosia, the state of not knowing they have a medical condition. > " In this sense, LLMorphism may contribute to a broader epistemic shift: from evaluating whether claims are grounded, justified, and accountable, to evaluating whether they are coherent, fluent, and plausible. " Grifters have always weaponized confident fluency over evidence. Anti-science plagues America right now. Some gullible few absorb the message that ivory-tower elites intentionally block heterodox research that is a paradigm shift, sowing seeds of doubt about academia. For example, I saw a doctor's YT channel that claimed high cholesterol isn't necessarily bad and that statins should be avoided all while recommending saturated fats over seed oils. Of course, he sells a book with his "suppressed" knowledge alongside having an online market selling US$90/month supplements that his book recommends. They claim academics keep them out of the journals out of self-preservation since the "paradigm shift" would cause their grants to go bye-bye. In reality, these charlatans combine cherry-picking of low-quality studies, telling a good story of the underdog fighting the establishment, and ignoring the body of evidence in support of the current expert consensus. Their grift is so illogical as if researchers wouldn't love to spark up a paradigm shift, becoming semi-famous and making more money, as if research isn't done decentralized across many countries funded by charities, different governments, and different corporations in competition with each other. Collusion without whistleblowers is simply impossible. Also, there's a difference between the corporate arm of medicine where they've been sued for billions before versus researchers who just follow the evidence to advance their research career and help everyone on the planet . Trust in expert consensus when it's this independent and decentralized and financed from all over the place with zero reason for an ulterior motive. They also pull off the, "Science has been wrong in the past." like Mac from It's always Sunny in Philadelphia. Science is in a state of constant flux where new evidence comes in, and the best guess, explaining as much evidence as possible right now, might change. > " Early childhood education is organized around relational pedagogy, attachment, affect regulation, and development (Cliffe & Solvanson, 2023). " One aspect here is, mass-produced cartoons for kids teach aplenty and do a decent job at it. I'm not convinced, in two decades from now, we won't have human-looking cyborgs doing teaching like this. > " The broader point, however, is that public debate on AI has focused mainly on anthropomorphism: whether we are giving too much mind to machines. " This part reminds me of some recent research out of Anthropic. They uncovered that a few hundred vectors in their activation space linked up to concrete emotional states. They dubbed them functional emotions while warning these have nothing to do with subjective experience of sentience. That paper had fantastic details in it, though. They tested things by adding a big magnitude to a particular functional emotion, running some tests, and seeing how its behavior changed. When "desperate," it not only hallucinated more as if it "felt" it must answer something, but it reward hacked more often. In a simulated situation, "desperate" Claude Opus blackmailed ~80% of the time whereas regular Opus did so ~20% while "calm" Opus did so ~0% (likely not zero, but they ran too few iterations of the test to approximate the probability). When curious / interested, it altered how it searched through the solution space by considering more options. It even went deeper into a promising solution before ending its calculations when allowed to do so .

kelseyfrog

Whether it works similarly or not, the default mode network has a functional similarity to an LLM: running text conditioned on sense inputs and emotional state. The more I practice Zhiné meditation, the more I feel certain that the default mode internal monologue is a distracting reflex. The times I've been the most present and calm are those where the constant chatter is extinguished and I'm just left to be. I can, in fact, operate and cogitate without a stream of language. Reflexively forming mental words certainly isn't "me" and sometimes even feels like a compulsion. It's also much more judgemental and wrong, the greater the distance I have from it. Having the ability to separate and eventually become adept at silencing that mental component will be a liberating step.