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Large language models lack deep insights or a theory of mind

arxiv.org

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Re: Large language models lack deep insights or a theory of mind

#51

Post by randcraw »

deeviant wrote: post #26

> A chief goal of artificial intelligence is to build machines that think like people. I disagree with the topic sentence. The goal should not be to "build machines that think like people", but to build machines that think, period. The way humans think is unlikely to be the optimal way to go about thinking anyways. Instead of talking about thinking, we should be talking about function. Less philosophy and more realit…

The topic sentence was the mantra of nearly all AI research back in the days of good-old-fashioned-AI, AKA symbolic AI. Understanding how reasoning is implemented by our brains was a much more compelling prospect than being able to implement 'intelligence' compositionally but without understanding how software achieved it -- which is largely where we find ourselves now. Today's AI is theory-free leaving us unenlightened about the continuum of intelligence -- across species, or within a human as our brain matures or goes pathological.

Many scientists outside the AI field have long shared an interest in the objective of how to "think like people" using software. Far fewer care if the AI is inexplicable (or if it can't be dissected into constituent components, thereby enabling us to explore the mind's constraints and dependencies among its cognitive processes).

Re: Large language models lack deep insights or a theory of mind

#52

Post by Tadpole9181 »

dsr_ wrote: post #20
hiddencost wrote: post #7

Another paper in a long series that confuses "our tests against currently available LLMs tuned for specific tasks found that they didn't perform well on our task" with "LLMs are architecturally unsuitable for our task".

There is no reason to believe (evidence) that any meaning ascribed to an LLM's utterances comes from the LLM rather than being pareidolia. If you've found some, please let everyone know.

There is no reason to believe (evidence) that any meaning ascribed to anyone but me's utterances comes from the person rather than being pareidolia.

If you've found some, please let everyone know.

Re: Large language models lack deep insights or a theory of mind

#53

Post by melenaboija »

Few weeks ago I did an experiment after a discussion here about LLMs and chess.

Basically inventing a board game and play against ChatGPT and see what happened. It was not able to do a single move, even having provided all the possible start moves in the prompt as part of the rules.

Not that I had a lot of hope about it, but it was definitely way worst than I expected.

If someone wants to take a look at it:

https://joseprupi.github.io/misc/2023/06/08/chat_gpt_board_g...

Re: Large language models lack deep insights or a theory of mind

#54

Post by hotpotamus »

dimal wrote: post #34
fnordpiglet wrote: post #19

In Buddhism there’s the idea that our core self is awareness, which is silent - it doesn’t think in a perceptible way, it doesn’t feel in a visceral way, but it underpins thought and feeling, and is greatly impacted by it. A large part of meditation and “release of suffering” is learning to let your awareness lead your thinking rather than your thinking lead your awareness. To be clear, I think this is in fact a corr…

I’ve been thinking along similar lines. It’s like with LLMs, they’ve created the part of the mind that is endlessly chattering, generating stories, sometimes true, sometimes false, but there’s no awareness or consciousness that ever steps back and can see thoughts as thoughts. And I don’t see how awareness or consciousness would arise from just more of the same (bigger models). It seems to be a fundamentally differen…

> It may appear to be aligned but then eventually it would probably get caught in a delusional feedback loop that it has no capacity to escape, because it can’t be aware of its own delusion.

I believe this is more or less the definition of human mental illness. I have to say that while I know it's really not possible, I wish people would stop pulling on these threads. I got into this line of work because I thought video games were cool, not because I wanted to philosophize about theories of mind and what intelligence is. I really don't like thinking about whether I'm just some sort of automaton made out of meat rather than metal and silicon.

Re: Large language models lack deep insights or a theory of mind

#55

Post by mcguire »

moffkalast wrote: post #16
omginternets wrote: post #6

Earlier quoted context omitted.

We don't "make up" consciousness, but yes, there is a processing latency of around 250-300ms.

I think they may be referring to the principle task that consciousness serves in humans, which is to rationalize decisions we've already made subconsciously to other people so they will help us. The conscious "why" comes after the decision. In that sense it's exactly the kind of bullshit machine that LLMs are.

A thought experiment: what kind of functional MRI result would convince you that human consciousness is real and an important part of decision making?

Note: if the result is someone reporting having made a decision before brain activity is seen, my next question is going to be "How does that work?"

Re: Large language models lack deep insights or a theory of mind

#56

Post by golergka »

melenaboija wrote: post #53

Few weeks ago I did an experiment after a discussion here about LLMs and chess. Basically inventing a board game and play against ChatGPT and see what happened. It was not able to do a single move, even having provided all the possible start moves in the prompt as part of the rules. Not that I had a lot of hope about it, but it was definitely way worst than I expected. If someone wants to take a look at it: https://j…

You haven't specified what model did you use, and the green ChatGPT icon in the shared conversation usually signifies GPT-3.5 model.

Here's my attempt at similar conversation — it seems GPT-4 is able to visualise the board and at least do a valid first move.

https://chat.openai.com/share/98427e21-678c-4290-aa8f-da8e93...

Re: Large language models lack deep insights or a theory of mind

#57

Post by famouswaffles »

throwanem wrote: post #50
famouswaffles wrote: post #43

Earlier quoted context omitted.

There does seem to be a general factor of intelligence in humans though that is the single biggest indicator of performance. Yes there are other factors too. >Here, the authors point out that the current batch of programs are not good at tasks that benefit from a theory of mind. Not good at tasks that benefit from a theory of mind extracted from visual data.

"Seem" is doing a lot of work here. So is the implicit claim that theory of mind in general can be demonstrated by current-gen foundation models, and only those aspects dependent on vision cannot.

I say seem but it's stronger than that. all evidence and testing points towards a general factor of intelligence. The better you perform at one "kind" of intelligence task, the better you will perform at them all. The shift in defining intelligence didn't come from nowhere. Yes, It's easy to think that there are multiple different mutually exclusive-ish kinds of intelligences and that you can excel in one and it has no bearing on performance on the other but that's not really true. all indication point otherwise. I'm not saying there aren't other factors but generally, that's what you can expect.

Yes theory of mind can be demonstrated. Make up whatever bespoke story you can with characters having varying levels if intention and knowledge. Then query GPT-4 about the state of the characters.

What i'm saying is that the vision component introduces another point of error, is it a lack of theory of mind ? or being yet unable to extract the necessary features from visual data ? They rapidly learn to but Blind people who could recognize squares by feel do not have the ability to recognize squares by sight upon gaining vision. https://www.projectprakash.org/_files/ugd/2af8ef_5a0c6250cc3...

Re: Large language models lack deep insights or a theory of mind

#58

Post by 33a »

Looking at their data and their experiments, I'd actually come to the opposite conclusion of the title. It's true that current LLMs are probably not quite at human level performance for these tasks, they're not that far off either and clearly we see as models increase in size and sophistication their performance on these tasks are improving.

So it seems like maybe a better title would be "LLMs don't have as advanced a theory of mind as a human does... for now..."

Re: Large language models lack deep insights or a theory of mind

#59

Post by FrustratedMonky »

uoaei wrote: post #36
tinco wrote: post #30

I think that if they would, that would be very surprising and indicative of a lot of wastefulness inside the model architecture. All these tests are simple single prompt experiments, so the LLM's get no chance to reason about their responses. They're just system 1 thinking, the equivalent of putting a gun to someone's head and asking them to solve a large division in 2 seconds. I bet a lot of these experiments would…

> They're just system 1 thinking, the equivalent of putting a gun to someone's head and asking them to solve a large division in 2 seconds. No, it's the equivalent of putting a gun to someone's head and asking them "what are my intentions?" Which is readily available to any being with a theory of mind.

Don't think so.

Put gun to persons ahead.

Ask them to do a division.

Then screaming at them "HOW DID YOU DO THAT, TELL ME NOW, OR YOU'RE TOAST".

Even most humans would splutter and not be able to answer.

Re: Large language models lack deep insights or a theory of mind

#60

Post by FrustratedMonky »

rf15 wrote: post #40
tinco wrote: post #30

I think that if they would, that would be very surprising and indicative of a lot of wastefulness inside the model architecture. All these tests are simple single prompt experiments, so the LLM's get no chance to reason about their responses. They're just system 1 thinking, the equivalent of putting a gun to someone's head and asking them to solve a large division in 2 seconds. I bet a lot of these experiments would…

they can't reason though, sadly - the premise does not hold.

So your premise is correct? Please back up the opposite. If you can, you should publish.

These responses are logically the same as "No You".

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