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A non-anthropomorphized view of LLMs

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Re: A non-anthropomorphized view of LLMs

#361

Earlier quoted context omitted.

As I write this, Claude Code is currently opening and closing various media files on my computer. Sometimes it plays the file for a few seconds before closing it, sometimes it starts playback and then seeks to a different position, sometimes it fast forwards or rewinds, etc. I asked Claude to write a E-AC3 audio component so I can play videos with E-AC3 audio in the old version of QuickTime I really like using. Claud…

Would it help you to know that trial and error is a common tactic by machines? Yes, humans do it too, but that doesn't mean the process isn't mechanical. In fact, in computing we might call this a "brute force" approach. You don't have to cover the entire search space to brute force something, and it certainly doesn't mean you can't have optimization strategies and need to grid search (e.g. you can use Bayesian metho…

It wasn't a simple brute force. When Claude was working this morning, it was pretty clearly only playing a file when it actually needed to see packets get decoded, otherwise it would simply open and close the document. Similarly, it would only seek or fast forward when it was debugging specific issues related to those actions. And it even "knew" which test files to open for specific channel layouts.

Yes this is still mechanical in a sense, but then I'm not sure what behavior you wouldn't classify as mechanical. It's "responding" to stimuli in logical ways.

But I also don't quite know where I'm going with this. I don't think LLMs are sentient or something, I know they're just math. But it's spooky.

Re: A non-anthropomorphized view of LLMs

#362

I have the technical knowledge to know how LLMs work, but I still find it pointless to not anthropomorphize, at least to an extent. The language of "generator that stochastically produces the next word" is just not very useful when you're talking about, e.g., an LLM that is answering complex world modeling questions or generating a creative story. It's at the wrong level of abstraction, just as if you were discussing…

Agreed. I'm also in favor of anthropomorphizing, because not doing so confuses people about the nature and capabilities of these models even more . Whether it's hallucinations, prompt injections, various other security vulnerabilities/scenarios, or problems with doing math, backtracking, getting confused - there's a steady supply of "problems" that some people are surprised to discover and even more surprised this is…

I disagree. Anthropomorphization can be a very useful tool but I think it is currently over used and is a very tricky tool to use when communicating with a more general audience.

I think looking at physics might be a good example. We love our simplified examples and there's a big culture of trying to explain things to the lay person (mostly because the topics are incredibly complex). But how many people have misunderstood an observer of a quantum event with "a human" and do not consider "a photon" as an observer? How many people think in Schrodinger's Cat that the cat is both alive and dead?[0] Or believe in a multiverse. There's plenty of examples we can point to.

While these analogies *can* be extremely helpful, they *can* also be extremely harmful. This is especially true as information is usually passed through a game of telephone[1]. There is information loss and with it, interpretation becomes more difficult. Often a very subtle part can make a critical distinction.

I'm not against anthropomorphization[2], but I do think we should be cautious about how we use it. The imprecise nature of it is the exact reason we should be mindful of when and how to use it. We know that the anthropomorphized analogy is wrong. So we have to think about "how wrong" it is for a given setting. We should also be careful to think about how it may be misinterpreted. That's all I'm trying to say. And isn't this what we should be doing if we want to communicate effectively?

[0] It is not. It is either. The point of this thought experiment is that we cannot know the answer without looking inside. There is information loss and the event is not deterministic. It directly relates to the Heisenberg Uncertainty Principle, Godel's Incompleteness, or the Halting Problem. All these things are (loosely) related around the inability to have absolute determinism.

[1] https://en.wikipedia.org/wiki/Telephone_game

[2] https://news.ycombinator.com/item?id=44494022

Re: A non-anthropomorphized view of LLMs

#363

Earlier quoted context omitted.

Would it help you to know that trial and error is a common tactic by machines? Yes, humans do it too, but that doesn't mean the process isn't mechanical. In fact, in computing we might call this a "brute force" approach. You don't have to cover the entire search space to brute force something, and it certainly doesn't mean you can't have optimization strategies and need to grid search (e.g. you can use Bayesian metho…

It wasn't a simple brute force. When Claude was working this morning, it was pretty clearly only playing a file when it actually needed to see packets get decoded, otherwise it would simply open and close the document. Similarly, it would only seek or fast forward when it was debugging specific issues related to those actions. And it even "knew" which test files to open for specific channel layouts. Yes this is still…

  > It wasn't a simple brute force.
I think you misunderstood me.

"Simple" is the key word here, right? You agree that it is still under the broad class of "brute force"?

I'm not saying Claude is naively brute forcing. In fact, with lack of interpretibility of these machines it is difficult to say what kind of optimization it is doing and how complex that it (this was a key part tbh).

My point was to help with this

  > I really don't want to anthropomorphize these programs, but it's just so hard when it's acting so much like a person...
Which requires you to understand how some actions can be mechanical. You admitted to cognitive dissonance (something we all do and I fully agree is hard not to do) and wanting to fight it. We're just trying to find some helpful avenues to do so.

  > It's "responding" to stimuli in logical ways.
And so too can a simple program, right? A program can respond to user input and there is certainly a logic path it will follow. Our non-ML program is likely going to have a deterministic path (there is still probabilistic programming...), but that doesn't mean it isn't logic, right?

But the real question here, which you have to ask yourself (constantly) is "how do I differentiate a complex program that I don't understand from a conscious entity?" I guarantee you that you don't have the answer (because no one does). But isn't that a really good reason to be careful about anthropomorphizing it?

That's the duck test.

How do you determine if it is a real duck or a highly sophisticated animatronic?

If you anthropomorphize, you rule out the possibility that it is a highly sophisticated animatronic and you *MUST* make the assumption that you are not only an expert, but a perfect, duck detector. But simultaneously we cannot rule out that it is a duck, right? Because, we aren't a perfect duck detector *AND* we aren't an expert in highly sophisticated animatronics (especially of the duck kind).

Remember, there are not two answers to every True-False question, there are three. Every True-False question either has an answer of "True", "False", or "Indeterminate". So don't naively assume it is binary. We all know the Halting Problem, right? (also see my namesake or quantum physics if you want to see such things pop up outside computing)

Though I agree, it can be very spooky. But that only increases the importance of trying to develop mental models that help us more objectively evaluate things. And that requires "indeterminate" be a possibility. This is probably the best place to start to combat the cognitive dissonance.

Re: A non-anthropomorphized view of LLMs

#364
Some of the arguments are very strange:

> Statements such as "an AI agent could become an insider threat so it needs monitoring" are simultaneously unsurprising (you have a randomized sequence generator fed into your shell, literally anything can happen!) and baffling (you talk as if you believe the dice you play with had a mind of their own and could decide to conspire against you).

> we talk about "behaviors", "ethical constraints", and "harmful actions in pursuit of their goals". All of these are anthropocentric concepts that - in my mind - do not apply to functions or other mathematical objects.

An AI agent, even if it's just "MatMul with interspersed nonlinearities" can be an insider threat. The research proves it:

[PDF] See 4.1.1.2: https://www-cdn.anthropic.com/4263b940cabb546aa0e3283f35b686...

It really doesn't matter whether the AI agent is conscious or just crunching numbers on a GPU. If something inside your system is capable of—given some inputs—sabotaging and blackmailing your organization on its own (which is to say, taking on realistic behavior of a threat actor), the outcome is the same! You don't need believe it's thinking, the moment that this software has flipped its bits into "blackmail mode", it's acting nefariously.

The vocabulary to describe what's happening is completely and utterly moot: the software is printing out some reasoning for its actions _and then attempting the actions_. It's making "harmful actions" and the printed context appears to demonstrate a goal that the software is working towards. Whether or not that goal is invented through some linear algebra isn't going to make your security engineers sleep any better.

> This muddles the public discussion. We have many historical examples of humanity ascribing bad random events to "the wrath of god(s)" (earthquakes, famines, etc.), "evil spirits" and so forth. The fact that intelligent highly educated researchers talk about these mathematical objects in anthropomorphic terms makes the technology seem mysterious, scary, and magical.

The anthropomorphization, IMO, is due to the fact that it's _essentially impossible_ to talk about the very real, demonstrable behaviors and problems that LLMs exhibit today without using terms that evoke human functions. We don't have another word for "do" or "remember" or "learn" or "think" when it comes to LLMs that _isn't_ anthropomorphic, and while you can argue endlessly about "hormones" and "neurons" and "millions of years of selection pressure", that's not going to help anyone have a conversation about their work. If AI researchers started coming up with new, non-anthropomorphic verbs, it would be objectively worse and more complicated in every way.

Re: A non-anthropomorphized view of LLMs

#365

> I am baffled that the AI discussions seem to never move away from treating a function to generate sequences of words as something that resembles a human. This is such a bizarre take. The relation associating each human to the list of all words they will ever say is obviously a function. > almost magical human-like powers to something that - in my mind - is just MatMul with interspersed nonlinearities. There's a ric…

> do you believe there's anything about humans that exists outside the mathematical laws of physics?

I don't.

The point is not that we, humans, cannot arrange physical matter such that it have emergent properties just like the human brain.

The point is that we shouldn't.

Does responsibility mean anything to these people posing as Evolution?

Nobody's personally responsible for what we've evolved into; evolution has simply happened. Nobody's responsible for the evolutionary history that's carried in and by every single one of us. And our psychology too has been formed by (the pressures of) evolution, of course.

But if you create an artificial human, and create it from zero, then all of its emergent properties are on you. Can you take responsibility for that? If something goes wrong, can you correct it, or undo it?

I don't consider our current evolutionary state "scripture", so we certainly tweak, one way or another, aspects that we think deserve tweaking. To me, it boils down to our level of hubris. Some of our "mistaken tweaks" are now visible at an evolutionary scale, too; for a mild example, our jaws have been getting smaller (leaving less room for our teeth) due to our bad up diet (thanks, agriculture). But worse than that, humans have been breeding plants, animals, modifying DNA left and right, and so on -- and they've summarily failed to take responsibility for their atrocious mistakes.

Thus, I have zero trust in, and zero hope for, assholes who unabashedly aim to create artificial intelligence knowing full well that such properties might emerge that we'd have to call artificial psyche. Anyone taking this risk is criminally reckless, in my opinion.

It's not that humans are necessarily unable to create new sentient beings. Instead: they shouldn't even try! Because they will inevitably fuck it up, bringing about untold misery; and they won't be able to contain the damage.

Re: A non-anthropomorphized view of LLMs

#366

Earlier quoted context omitted.

I mean you can boil anything down to it's building blocks and make it seem like it didn't 'decide' anything. When you as a human decide something, your brain and it's neurons just made some connections with an output signal sent to other parts that resulting in your body 'doing' something. I don't think LLMs are sentient or any bullshit like that, but I do think people are too quick to write them off before really th…

I wasn't talking about knowing (they clearly encode knowledge), I was talking about thinking/reasoning, which is something LLMs do not in fact do IMO. These are very different and knowledge is not intelligence.

To me all of those are so vaguely defined that arguing whether an LLM is "really really" doing something is kind of a waste of time.

It's like we're clinging on to things that make us feel like human cognition is special so we're saying LLM's arent "really" doing it, then not defining what it actually is.

Re: A non-anthropomorphized view of LLMs

#367

I have the technical knowledge to know how LLMs work, but I still find it pointless to not anthropomorphize, at least to an extent. The language of "generator that stochastically produces the next word" is just not very useful when you're talking about, e.g., an LLM that is answering complex world modeling questions or generating a creative story. It's at the wrong level of abstraction, just as if you were discussing…

The "point" of not anthropomorphizing is to refrain from judgement until a more solid abstraction appears. The problem with explaining LLMs in terms of human behaviour is that, while we don't clearly understand what the LLM is doing, we understand human cognition even less! There is literally no predictive power in the abstraction "The LLM is thinking like I am thinking". It gives you no mechanism to evaluate what ta…

> It is like someone inventing the aeroplane and someone looks at it and says "oh, it's flying, I guess it's a bird". It's not a bird!

We tried to mimic birds at first; it turns out birds were way too high-tech, and too optimized. We figured out how to fly when we ditched the biological distraction and focused on flight itself. But fast forward until today, we're reaching the level of technology that allows us to build machines that fly the same way birds do - and of such machines, it's fair to say, "it's a mechanical bird!".

Similarly, we cracked computing from grounds up. Babbage's difference engine was like da Vinci's drawings; ENIAC could be seen as Wright brothers' first flight.

With planes, we kept iterating - developing propellers, then jet engines, ramjets; we learned to move tons of cargo around the world, and travel at high multiples of the speed of sound. All that makes our flying machines way beyond anything nature ever produced, when compared along those narrow dimensions.

The same was true with computing: our machines and algorithms very quickly started to exceed what even smartest humans are capable of. Counting. Pathfinding. Remembering. Simulating and predicting. Reproducing data. And so on.

But much like birds were too high-tech for us to reproduce until now, so were general-purpose thinking machines. Now that we figured out a way to make a basic one, it's absolutely fair to say, "I guess it's like a digital mind".

Re: A non-anthropomorphized view of LLMs

#368

To claim that LLMs do not experience consciousness requires a model of how consciousness works. The author has not presented a model, and instead relied on emotive language leaning on the absurdity of the claim. I would say that any model one presents of consciousness often comes off as just as absurd as the claim that LLMs experience it. It's a great exercise to sit down and write out your own perspective on how con…

Author here. What's the difference, in your perception, between an LLM and a large-scale meteorological simulation, if there is any? If you're willing to ascribe the possibility of consciousness to any complex-enough computation of a recurrence equation (and hence to something like ... "earth"), I'm willing to agree that under that definition LLMs might be conscious. :)

My personal views are an animist / panpsychist / pancomputationalist combination drawing most of my inspiration from the works of Joscha Bach and Stephen Wolfram (https://writings.stephenwolfram.com/2021/03/what-is-consciou...). I think that the underlying substrate of the universe is consciousness, and human and animal and computer minds result in structures that are able to present and tell narratives about themselves, isolating themselves from the other (avidya in Buddhism). I certainly don't claim to be correct, but I present a model that others can interrogate and look for holes in.

Under my model, these systems you have described are conscious, but not in a way that they can communicate or experience time or memory the way human beings do.

My general list of questions for those presenting a model of consciousness are: 1) Are you conscious? (hopefully you say yes or our friend Descartes would like a word with you!) 2) Am I conscious? How do you know? 3) Is a dog conscious? 4) Is a worm conscious? 5) Is a bacterium conscious? 6) Is a human embryo / baby consious? And if so, was there a point that it was not conscious, and what does it mean for that switch to occur?

What is your view of consciousness?

Re: A non-anthropomorphized view of LLMs

#369
post #152

To claim that LLMs do not experience consciousness requires a model of how consciousness works. The author has not presented a model, and instead relied on emotive language leaning on the absurdity of the claim. I would say that any model one presents of consciousness often comes off as just as absurd as the claim that LLMs experience it. It's a great exercise to sit down and write out your own perspective on how con…

> To claim that LLMs do not experience consciousness requires a model of how consciousness works. Nope. What can be asserted without evidence can also be dismissed without evidence. Hitchens's razor. You know you have consciousness (by the very definition that you can observe it in yourself) and that's evidence. Because other humans are genetically and in every other way identical, you can infer it for them as well.…

It seems like you are doing a lot of inferring about mammals experiencing consciousness, and you have drawn a line somewhere beyond these, and made the claim that your process is scientific. Could I present you my list of questions I presented to the OP and ask where you draw the line, and why here?

My general list of questions for those presenting a model of consciousness are: 1) Are you conscious? (hopefully you say yes or our friend Descartes would like a word with you!) 2) Am I conscious? How do you know? 3) Is a dog conscious? 4) Is a worm conscious? 5) Is a bacterium conscious? 6) Is a human embryo / baby consious? And if so, was there a point that it was not conscious, and what does it mean for that switch to occur?

I agree about the confusion of consciousness with intelligence, but these are complicated terms that aren't well suited to a forum where most people are interested in javscript type errors and RSUs. I usually use the term qualia. But to your example about existing for a few seconds without a train of thought; the Buddhists call this nirvana, and it's quite difficult to actually achieve.

Re: A non-anthropomorphized view of LLMs

#370
The missing bit is culture: the concepts, expectations, practices, attitudes… that are evolved over time by a human group and which each one of us has picked up throughout our lifetimes, both implicitly and explicitly.

LLMs are great at predicting and navigating human culture, at least the subset that can be captured in their training sets.

The ways in which we interact with other people are culturally mediated. LLMs are not people, but they can simulate that culturally-mediated communication well enough that we find it easy to anthropomorphise them.

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