In the old days, knowledge was
… the theoretical or practical understanding of a subject.
We now realize that this is an artificial construct. We now know that “subjects” are a man-made construct. And while we can master a subject, as defined by the current state of the art in that area, this will not necessarily give us better knowledge of the universe.
To see that, check out Feynman on modeling
In other words, there are times when data confirm two different models of reality. Neither can be said to be wrong at that stage.
Machine learning is taking this idea a step further. Machines can find patterns in data that go way beyond human capacity to understand based on models. And the machines are indifferent to the models that we use to understand data.
As long as our computer models instantiated our own ideas, we could preserve the illusion that the world works the way our knowledge —and our models — do. Once computers started to make their own models, and those models surpassed our mental capacity, we lost that comforting assumption. Our machines have made obvious our epistemological limitations, and by providing a corrective, have revealed a truth about the universe.
The world didn’t happen to be designed, by God or by coincidence, to be knowable by human brains. The nature of the world is closer to the way our network of computers and sensors represent it than how the human mind perceives it. Now that machines are acting independently, we are losing the illusion that the world just happens to be simple enough for us wee creatures to comprehend.
It has taken a network of machines that we ourselves created to let us see that we are the aliens
Errr … did you get that?