It is an easy way to understand the depth of the intellect you are speaking with and the knowledge set they are basing their answers on. Plus the answer "Yes, I always lie" is obviously a lie and proves that it is capable of contradicting itself even within the confines of one answer.
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But you're not speaking to an intellect. That's just anthropomorphising a neural network, which is anything but intelligent.
You're writing strings that a prediction generator uses as input to generate a continuation string based on lots of text written by humans. Yes, it looks like there was some magical "AI" that communicates, but that is not what is happening.
Humans get smart by absorbing language produced by other humans. It's what raises us above animals. A human who doesn't have that becomes feral, so much of what we consider to be human is learned culturally.
Humans also overfit to the training data. We all know some kids just learn how to apply a specific method for solving math problems and the moment the problem changes a bit, they are dumbfounded. They only learn the surface without understanding the essence, like language models.
Some learn foreign languages this way, and as a result they can only solve classroom exercises, they can't use it in the wild (Japanese teachers of English, anecdotally).
Another surprising human limitation is causal reasoning. If it were so easy to do it, we wouldn't have the anti-vax campaigns, climate change denial, religion, etc. We can apply causal reasoning only after training and in specific domains.
Given these observations I conclude that there is no major difference between humans and artificial agents with language models. GPT-3 is a language model without embodiment and memory so it doesn't count as an agent yet.
I think we probably agree here, but I'd like to make an adjacent point: Animals have been known for a while to communicate, and even have languages of their own. Mutes are no feral humans either. It's definitely more nuanced than that, and I follow that actual intelligence consists of more than just the ability to form coherent sentences.
One essential ingredient I think - "skin". The agent got to have skin in the game, to have something to win or lose, something that matters. For humans it is life, survival, reproduction. The necessities of life made us what we are now.
Humans don't just generate language out of the void. The use of language is grounded by various other inputs (senses, previous knowledge/understanding). So when a human is constructing sentences those sentences aren't just using earlier elements of the conversation to generate the next sentence (as language models do) but rather a vast wealth of resources previously accumulated.
AI that wants to actually generate language with human-like intelligence needs more inputs than just language to its model. Sure that information can also be overfit, but the lack of other inputs goes beyond just the computer model overfitting it's data.
> That's just anthropomorphising a neural network, which is anything but intelligent.
What is intelligence? GPT-3 seems to perform better than my dog at a load of these tasks, and I think my dog is pretty intelligent (at least for a dog).
I mean, to me this does seem to show a level of what intelligence means to me - i.e. an ability to pick up new skills and read/apply knowledge in novel ways.
Intelligence != sentience.
That's an interesting point, and I sure imply sentience when I say intelligence, to a certain degree. I'd argue that GPT-3 does not actually "understand" it's output in any way, it just tricks you into believing it does, for example by having some kind of a short-term memory, or forming coherent sentences. Yet the model has no abstract concept of the things it writes about. It's all just probabilities.
Yeah, it's basically Clever Hans. You can see it with the amount of completely nonsensical output you can also randomly get from it if you deviate even a small amount form the input data distribution.
> It is an easy way to understand the depth of the intellect you are speaking with
Sorry but no. An algorithm that, for a given prompt, finds and returns the semantically closest quote from a selection of 30 philosophers may sound very wise but is actually dumb as bricks. GPT-3 is obviously a bit more than that, but "depth of intellect" is not what you are measuring with chat prompts.
> Plus the answer "Yes, I always lie" is obviously a lie and proves that it is capable of contradicting itself even within the confines of one answer.
Contradicting yourself is not a feat if you don't have any concept of truth in the first place.
> Plus the answer "Yes, I always lie" is obviously a lie and proves that it is capable of contradicting itself even within the confines of one answer.
If it was a human to human conversation that answer would "just" be considered sarcasm.