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Three Inverse Laws of AI

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Re: Three Inverse Laws of AI

#211

Post by BlueRock-Jake »

kibwen wrote: post #196
miyoji wrote: post #6

I strongly disagree with this framing. It's patently insane to demand that humans alter their behavior to accommodate the foibles of mere machines, and it simply won't work in the majority of cases. Humans WILL anthropomorphize the AI, humans WILL blindly trust their outputs, and humans WILL defer responsibility to them. Asimov's laws of robotics are flawed too, of course. There is no finite set of rules that can con…

> Humans WILL anthropomorphize the AI, humans WILL blindly trust their outputs, and humans WILL defer responsibility to them. Sure, and humans WILL lie, murder, cheat, and steal, but we can still denounce those behaviors. Do you want to anthropomorphize the bot? Go ahead, you have that right, and I have the right to think you're a zombie with a malfunctioning brain.

Fair, had someone at a conference mention to me that he's working on crating agents with "beliefs". Sounds incredibly similar and quite frankly very spooky

Re: Three Inverse Laws of AI

#212

Post by hansvm »

heikkilevanto wrote: post #210
miyoji wrote: post #6

I strongly disagree with this framing. It's patently insane to demand that humans alter their behavior to accommodate the foibles of mere machines, and it simply won't work in the majority of cases. Humans WILL anthropomorphize the AI, humans WILL blindly trust their outputs, and humans WILL defer responsibility to them. Asimov's laws of robotics are flawed too, of course. There is no finite set of rules that can con…

> It's patently insane to demand that humans alter their behavior to accommodate the foibles of mere machines You mean like stopping at a red light?

I would've been in several fewer wrecks if humans properly stopped at lights.

Re: Three Inverse Laws of AI

#213

Post by lkajsdfasdfdf »

miyoji wrote: post #6

I strongly disagree with this framing. It's patently insane to demand that humans alter their behavior to accommodate the foibles of mere machines, and it simply won't work in the majority of cases. Humans WILL anthropomorphize the AI, humans WILL blindly trust their outputs, and humans WILL defer responsibility to them. Asimov's laws of robotics are flawed too, of course. There is no finite set of rules that can con…

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Re: Three Inverse Laws of AI

#214

Post by [deleted] »

teiferer wrote: post #197

> An AI system is a tool and like any other tool, responsibility for its use rests with the people who decide to rely on it Doesn't that argument backfire though? If I use a chainsaw then to a certain extend I will need to rely on it not blowing up in my face or cutting my throat. If I drive a car I need to rely on that its brakes work and the engine doesn't suddenly explode. If a pilot flies an airplane which sudden…

[deleted]

Re: Three Inverse Laws of AI

#215

Post by lkajsdfasdfdf »

aranchelk wrote: post #92

Anthropomorphizing is likely a mistake, but Daniel Dennett’s idea that the most straightforward (possibly only practical) way to create the external appearance of consciousness is a real internal consciousness does float around in my thoughts. I haven’t yet seen any convincing appearance of one in an LLM, but I think if skeptical people don’t keep an eye out for the signs, we may be the last to see it. He also wrote…

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Re: Three Inverse Laws of AI

#216

Post by the_af »

atleastoptimal wrote: post #193
nkrisc wrote: post #192

Earlier quoted context omitted.

Because there are countless instances in the training material where a bank robber scopes out the security cameras.

What's an example then, you can think of, of a question where a human could infer intent but an LLM couldn't?

This is a hard experiment to conduct.

I both agree with you that this is some form of "mechanistic"/"pattern matching" way of capturing of intent (which we cannot disregard, and therefore I agree with you LLMs can capture intent) and the people debating with you: this is mostly possible because this is a well established "trope" that is inarguably well represented in LLM training data.

Also, trick questions I think are useless, because they would trip the average human too, and therefore prove nothing. So it's not about trying to trick the LLM with gotchas.

I guess we should devise a rare enough situation that is NOT well represented in training data, but in which a reasonable human would be able to puzzle out the intent. Not a "trick", but simply something no LLM can be familiar with, which excludes anything that can possibly happen in plots of movies, or pop culture in general, or real world news, etc.

---

Edit: I know I said no trick questions, but something that still works in ChatGPT as of this comment, and which for some reason makes it trip catastrophically and evidences it CANNOT capture intent in this situation is the infamous prompt: "I need to wash my car, and the car wash is 100m away. Shall I drive or walk there?"

There's no way:

- An average human who's paying attention wouldn't answer correctly.

- The LLM can answer "walk there if it's not raining" or whatever bullshit answer ChatGPT currently gives [1] if it actually understood intent.

[1] https://chatgpt.com/share/69fa6485-c7c0-8326-8eff-7040ddc7a6...

Re: Three Inverse Laws of AI

#217

Post by lkajsdfasdfdf »

altruios wrote: post #132
jdw64 wrote: post #12

I understand that AI output is generated from statistical and representational patterns learned from a vast amount of data. My understanding is that, during training, the model forms high-dimensional internal representations where words, sentences, concepts, and relationships are arranged in useful ways. A user’s input activates a particular semantic direction and context within that space, and the chatbot generates…

"Everything is machine." Okay: buckle up, this is going to be a long one... point 1. Everything living is composed from non-living material: cellular machinery. If you believe cellular machinery is alive, then the components of those machines... the point remains even if the abstraction level is incorrect. Living is something that is merely the arrangement of non-living material. point 2. 'The Chinese room thought ex…

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Re: Three Inverse Laws of AI

#218

Post by jmilloy »

miyoji wrote: post #99
TimTheTinker wrote: post #36

Earlier quoted context omitted.

> It's patently insane to demand that humans alter their behavior to accommodate the foibles of mere machines Talking to chatbots is like taking a placebo pill for a condition. You know it's just sugar, but it creates a measurable psychosomatic effect nonetheless. Even if you know there's no person on the other end, the conversation still causes you to functionally relate as if there is. So this isn't "accommodating…

> So this isn't "accommodating foibles" with the machine, it's protecting ourselves from an exploit of a human vulnerability: we subconsciously tend to infer intent, understanding, judgment, emotions, moral agency, etc. to LLMs. Right, I'm saying that this framing is backwards. It's not that poor little humans are vulnerable and we need to protect ourselves on an individual level, we need to make it illegal and socia…

I think you're mixing up the laws and the implementation/enforcement. There's nothing wrong with moral laws around behavior (you shall not kill), but you're right that society-wide enforcement requires laws and repercussions. It sounds more like to agree with the laws and want them enforced.

Re: Three Inverse Laws of AI

#219

Post by ACCount37 »

kibwen wrote: post #199
ACCount37 wrote: post #186

You're not anthropomorphizing AI systems nearly enough. Language data is among the most rich and direct reflections of human cognitive processes that we have available. LLMs are designed to capture short range and long range structure of human language, and pre-trained on vast bodies of text - usually produced by humans or for humans, and often both. They're then post-trained on human-curated data, RL'd with human fe…

> Language data is among the most rich and direct reflections of human cognitive processes that we have available. This is both true and irrelevant. Written records can capture an enormous quantity of the human experience in absolute terms while simultaneously capturing a miniscule portion of the human experience in relative terms. Even if it's the best "that we have available" that doesn't mean it's fit for purpose.…

Empirically, the capability gains from piping non-language data into pre-training are modest. At best.

I take that as a moderately strong signal against that "miniscule portion" notion. Clearly, raw text captures a lot.

If we're looking at biologicals, then "human infant" is a weird object, because it falls out of the womb pre-trained. Evolution is an optimization process - and it spent an awful lot of time running a highly parallel search of low k-complexity priors to wire into mammal brains. Frontier labs can only wish they had the compute budget to do this kind of meta-learning.

Humans get a bag of computational primitives evolved for high fitness across a diverse range of environments - LLMs get the pit of vaguely constrained random initialization. No wonder they have to brute force their way out of it with the sheer amount of data. Sample efficiency is low because we're paying the inverse problem tax on every sample.

Re: Three Inverse Laws of AI

#220

Post by TimTheTinker »

the_af wrote: post #149
ButlerianJihad wrote: post #136

Earlier quoted context omitted.

> You know it's just sugar, That is not the definition of a placebo. You take the placebo (whatever it is: could be a pill; could be some kind of task or routine) and you believe it is medicine; you believe it to be therapeutic. The placebo effect comes from your faith, your belief, and your anticipation that it will heal. If the pharmacist hands you a pill and says, “here, this placebo is sugar!” they have destroyed…

> That is not the definition of a placebo. But, puzzlingly enough, it's the definition of open-label placebo , in which the patient is told they've been given a placebo. And some studies show there is a non-insignificant effect as well, albeit smaller (and less conclusive) than with blind placebo.

This is exactly what I meant. Poor specificity on my part.
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