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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

#61

Post by FrustratedMonky »

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…

I'm older.

I've bought 'new' board games for kids.

Then, I have been un-able to play because the instructions were pretty bad.

Humans also need to 'learn'. Need a few play-throughs.

No human is going out and 'in a vacuum' with no experience, buying Risk and from scratch, read instructions and play perfect game winning strategy.

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

#62

Post by mcguire »

JonChesterfield wrote: post #3

The fun question is whether human cognition similarly lacks deep insights or said theory of mind. I perceive a moving of the goalposts as machine intelligence improves. Once we'd have been happy with smarter than an especially stupid person, now I think we're aiming at smarter than the smartest person.

I believe those goalposts have always been way farther out than many people think. If you look at the discussion around Turing's original Imitation Game paper, you'll find people wanting the machine to be able to do things that most humans cannot. And its perfectly valid to do so.

If you regard "an especially stupid person" as someone with significant cognitive or communication limits, then Parry and Eliza's Doctor are pretty fair simulations of paranoid schizophrenia (as it was understood at the time) and Rogerian therapy. Likewise, chess and go AIs are pretty damn smart, except they can't do anything else.

The point is that, if you accept limits on what the machine needs to do, then "intelligence" as defined by behavior you can recognize becomes trivially and meaninglessly easy.

(It's sort of like evaluating a person's competence: a minority person has to be more competent than their cohort because non-minority people get the benefit of the doubt.)

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

#63

Post by kens »

swatcoder wrote: post #21
menssen wrote: post #9

I appreciate this paper for relatively clearly stating what "human-like" might entail, which in this case involves "reasoning about the causes behind other people's behavior" which is "critical to navigate the social world" as outlined in this citation: https://www.sciencedirect.com/science/article/abs/pii/S00100... I get frustrated often when people argue "well, it isn't really intelligent" and then give examples th…

The underlying problem is that "intelligence" is itself a crappy, poorly defined word with a fraught and inconsistent history. It doesn't appear until the early 20th century, in the shadow of compulsory education and the challenges it presented, first as a technical label for attempts to sort students -- and later soldiers -- into the tracks in which they're most likely to succeed, and then being haphazardly asserted…

> It [the word "intelligence"] doesn't appear until the early 20th century

I'm not sure what you mean here, since the word dates back to the late 14th century with roughly the same meaning as now. Perhaps you're thinking of "intelligence quotient"?

https://www.etymonline.com/word/intelligence

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

#64

Post by famouswaffles »

33a wrote: post #58

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…

Indeed. Not sure what i was expecting reading the title but "GPT-4V is close to or matching human median performance on most of these tasks" was not it.

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

#65

Post by swatcoder »

pixl97 wrote: post #49
swatcoder wrote: post #21

Earlier quoted context omitted.

The underlying problem is that "intelligence" is itself a crappy, poorly defined word with a fraught and inconsistent history. It doesn't appear until the early 20th century, in the shadow of compulsory education and the challenges it presented, first as a technical label for attempts to sort students -- and later soldiers -- into the tracks in which they're most likely to succeed, and then being haphazardly asserted…

Most of what you're saying here is describing the alignment issue. We (mostly) don't want unaligned A(G|S)I. The outcomes of that could be extenstential.

Only for those mundane senses of alignment where we say "This system is reliable in tasks that look like X and unreliable in tasks that look like Y, so let's craft hard boundaries to avoid naive use for Y"

But it's skeptical of the other sense alignment, where a potential Master Strategist needs to be trained or crippled before it outsmarts us. It sees that perspective as comparable to logicians debating whether we might live in the domain of a benevolent or evil omnipotence: "if an ant is more powerful than a rock, and I'm more powerful than an ant, then perhaps there is something so powerful that it encompasses all opportunities to influence the universe including the power to hide itself from me." -- which comes from taking a concrete measure, assuming that it's an independent variable, and then inductively extending it to an infinite or otherwise unevidenced scale. This technique is undisprovable and so it's easy for "rational" people to mine work from it for a very long time, but history and analysis give room for skeptics to be like "WTF you going on about; let's have some tea"

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

#66

Post by joduplessis »

For me, the entire AGI conversation is hyperbolic / hype. How can we infer intelligence to something when we, ourselves, have such a poor (none) grasp of what makes us conscience? I'm associating intelligence with consciousness - because it seems correlated. Are we really ready to associate "AGI" with solving math problems ("new Q algo.")? That seems incredibly naive & reinforces my opinion that LLM's are much more like crypto, than actual progress.

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

#67

Post by pixl97 »

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…

https://en.wikipedia.org/wiki/Moravec%27s_paradox

While you're adding a bunch of eastern philosophy to it, we need to take a step back from 'human' intelligence and go to animal and plant intelligence to get a better idea of the massive variation in what covers thought. In animal/insects we can see that thinking is not some binary function of on or off. It is an immense range of different electrical and chemical processes that involve everything from the brain and the nerves along with chemical signaling from cells. In things like plants and molds 'thinking' doesn't even involve nerves, it's a chemical process.

A good example of this at the human level is a reflex. Your hand didn't go back to your brain to ask for instructions on how to get away from the fire. That's encoded in the meat and nerves of your arm by systems that are much older than higher intelligence. All the systems for breath, drink, eat, procreate were in place long before high level intelligence existed. Intelligence just happens to be a new floor stacked hastily on top of these legacy systems that happened to be beneficial enough it didn't go extinct.

Awareness is another one of those very deep rabbit hole questions. There are 'intelligent' animals without self awareness, but with awareness of the world around them. And they obviously have agency. Of course this is where the AI existentialists come in and say wrapping up agency, awareness, and superintelligence may not work out for humans as well as we expect.

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

#68

Post by passion__desire »

fredliu wrote: post #42

I have small kids, toddlers, who can already speak the language but still developing their "sense of the world" or "theory of mind" if you will. Maybe it's just me, but talking to toddlers often reminds me of interacting with LLMs, where you would have this realization from time to time "oh, they don't get this, need to break down more to explain". Of course LLM has more elaborate language skills due to its exposure…

It's not just true about toddlers but also for adults in particular time frame. Maturity of thought is cultural phenomenon. Descartes used to think animals are automaton while they behaved exactly like humans in almost all aspects in which he could investigate animals and humans during those times and yet he reached illogical conclusion.

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

#69

Post by pixl97 »

hotpotamus wrote: post #54
dimal wrote: post #34

Earlier quoted context omitted.

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 vi…

Ah, the first releases of the Bing AI were fun here as they plunged into feedback loops of madness that were scarily human sounding. Thank you humanity for making artificial insanity.

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

#70

Post by thewakalix »

swatcoder wrote: post #21
menssen wrote: post #9

I appreciate this paper for relatively clearly stating what "human-like" might entail, which in this case involves "reasoning about the causes behind other people's behavior" which is "critical to navigate the social world" as outlined in this citation: https://www.sciencedirect.com/science/article/abs/pii/S00100... I get frustrated often when people argue "well, it isn't really intelligent" and then give examples th…

The underlying problem is that "intelligence" is itself a crappy, poorly defined word with a fraught and inconsistent history. It doesn't appear until the early 20th century, in the shadow of compulsory education and the challenges it presented, first as a technical label for attempts to sort students -- and later soldiers -- into the tracks in which they're most likely to succeed, and then being haphazardly asserted…

> and it wants to kill everyone

It wouldn't have to want to kill everyone. As long as it doesn't want to not kill everyone, the side effects of it getting what it wants could be catastrophic.

> and we don't notice

How well do we understand what's going on inside ChatGPT? How well will we understand the next?

> and forget to shut it off

Earlier I would have argued that sufficiently advanced AI could prevent itself from being shut off via Things You Didn't Expect, and would instrumentally want to preserve its existence. But these days, people are giving ChatGPT not just internet access but even actively handing it control over various processes. At this rate, the first superhuman AI will face not an impermeable box but a million conveniently labeled levers!

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