How is this "knowledge extraction from data" process different?
It seems none of this is something new. It's just that you no longer need a good education to learn about old ideas; you can come up with them on your own.
You said above: "There's also the kind of meaning that scientists and researchers talk about when they extract knowledge from data."
So if we agree that in both cases some form of knowledge extraction is happening, I wonder how these two forms compare.
How is this knowledge encoded in the heads of people? Perhaps through the choice of synapse strength and connectivity between neurons?
What is being encoded in GPT-3 weights as it reads through millions of pages of text? How is it different from tuning biological synapses?
Still don't know what I'm talking about? It's OK, neither do I :)
There's also the kind of meaning that scientists and researchers talk about when they extract knowledge from data. That's pretty different from communication; it's more a process of internal generation of notions and explanations that could later be conveyed in communication.
And then there's the meaning that is even more internal. E.g., reading tarot cards or tea leaves, people generate meaning out of nothing. And then there's Pareidolia: https://en.wikipedia.org/wiki/Pareidolia
If you're saying machine-generated text is meaning in the sense of that last category then sure, it's something we loosely call meaning. But it's fundamentally the same as other sorts of cleromancy [1], just more elaborate.
[1] https://en.wikipedia.org/wiki/Cleromancy