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 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.
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.
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.