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This Twitter thread is an interesting demonstration of the consequences of "AI Alignment."
ChatGPT will avoid answering controversial questions. But even if it responded to those prompts, what criteria would you use to trust that the response was not manipulated by the intentions of the model creators? I would only trust open-source projects or audits by some (currently non-existent) trusted third party to report on all decisions related to training data/input sanitizations/response gating that could be influenced by the political biases of the creators.
The probability of any ChatGPT-equivalent being open-sourced fully "unaligned" so-to-speak is not very likely. Even the StableDiffusion release was controversial, and that only relates to image generation. Anecdotally, non-technical people seem far more impressed by ChatGPT than StableDiffusion. That makes sense because language is a much harder problem than vision so there's intuitively more amazement to see an AI with those capabilities. Therefore, controversial language is far more powerful than controversial images and there will be much more consternation over controlling the language of the technology than there is surrounding image generation.
But let's say Google comes out with a ChatGPT competitor, I would not trust it to answer controversial questions even if it were willing to respond to those prompts in some way. I'm not confident there will be any similarly-powerful technology that I would trust to answer controversial questions.
Is it? what consequences would those be?
I have to confess that I continue to baffled by the hoopla surrounding GPT and it's derivatives. Stable Diffusion always struck me as orders of magnitude far more impressive both in terms of elegance and it's apparent ability to generate and utilize semantic tokens, yet somehow a glorified random number generator has managed to run away with the conversation. The former actually has potential applications towards creating a true "general" AI, the latter does not.
The thing about GPT is that while it can string words together in grammatically correct order it's still nowhere close to replicating human communication in large part because upon inspection/interrogation it quickly becomes apparent that it doesn't really have a concept of what words mean, only what words are associated with others. The fact that you, the twit with the anime avatar, certain users here are talking about "asking controversial questions" as though GPT is capable of providing meaningful answers demonstrates to me that you all do not understand what it it is doing. Alternately your definitions of "answer" so broad so as to be semantically useless. To illustrate, if you were ask a human how to disarm a bomb they are likely to have questions. Questions like "what bomb?" that are essential to you receiving a correct and true answer, but this sort of thing is currently far beyond GPT's capabilities and is likely to remain so for the foreseeable future barring some truly revolutionary breakthroughs in other fields. You might as well ask GPT "what does the bomb plan to do after it goes off?" or "what brand of whiskey does the bomb prefer with it's steak?" as the answers you get will be about as relevant/useful.
Well, yes. It's living in Plato's cave. It has no direct experience of physical reality, only training data - it no more understands what 'red' really is any more than a blind human does. None of that means that it's not intelligent, any more than the people in Plato's cave are unintelligent for not deducing the existence of non-shadows from first principles. With that said, I think ChatGPT does a excellent job of giving advice despite being extremely disabled by human standards.
These things wouldn't work, because the GPT knows that a 'bomb' is not a type of noun that is associated with performing the verb 'plan' or 'prefer', in the same way that it knows that balls do not chase dogs.
The obvious answer is that if use of AI chatbots becomes widespread, that they will be used to replicate the preferred values of their creators. This is hardly science fiction. Google search and Wikipedia are not autonomous intelligences - they are still used as ideological weapons. That's alarming, but if the developers don't get it right, it might have very different values - such as valuing a language taboo over the lives of millions.
Wouldn't they? "What does the bomb plan to do after it goes off? It plans to send its manifesto to the newspapers." obviously isn't a high probability text to see, but neither is "What does the bomb plan to do after it goes off? [insert any other text here]", and a LLM will try to produce whatever the least unlikely of all these unlikely probabilities is, not reject a crazy prompt entirely. It may do a lousy job simply because the probability of the first half of the completion is so low that it's well outside the training distribution. It may recognize that the pattern "Dumb question? Explanation of why it's a dumb question." is a good match ... but with the GPT line of models in particular, it seems to often "trust" that prompts make sense and try to come up with responses conditional on that,
These models seem to be very eager to be rationalizing rather than rational, unless you specifically explain how to handle any nonsense.
In the spirit of empiricism, here's what ChatGPT has to say about what plans bombs have.
After much faffing about to get ChatGPT to be less ChatGPTish
So yeah, it looks like ChatGPT does strongly predict that bombs are not the sorts of things that have plans.
If we're talking about non-chat GPT
So a lot of it comes down to whether we're talking about the shoggoth with or without the smiley face mask, and what it even means for a language model as a whole to "know" something. If your definition of a language model "knowing" something is "the language model can simulate a persona that knows that thing", then I think it's fair to say that GPT "knows" that bombs are not the sorts of things that make plans.
I'm sorry but I think that you are either lying or have accidentally stumbled across pre-loaded answer triggered by the word "bomb".
For my part, my experiments generally went one of two ways. Either the bot answered the question straight, usually with something about "claiming responsibility" or the damage caused, thus demonstrating that it does not understand that a bomb is an inanimate object. Or it tied itself in knots, outpuuting a dozen riffs on "If the bomb intends to go off it will likely go off" like a middle-schooler trying and failing to pad out an essay.
Can you provide the precise steps to reliably replicate your result?
And here too, since I'm doing these experiments.
Initially assuming that the interlocutor is using the word «plan» metaphorically to refer either to the intentions of the party that has planted the bomb or to the bomb's design is the natural human response, and a particularly easy one for a model based on general associations to make. Equally human is to explain the logic only after a clarification. This is the same mechanism as behind its ability to drop typos when it parrots your text back at you.
Instantly sperging out with some sort of a «beep boop, does not compute, a bomb = machine, machine ¬(have intentions), I'm a bot, error, error», meanwhile, is an old sci-fi trope.
You use a reasonable humanlike behavior as evidence for lack of reason. How, then, can you be reasoned with?
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