Science works by scientists not doing all their thinking for themselves. That’s also how it fails. Getting the balance right may be hard, but no-one has really tried very hard, so it may not be. Trying to do that is largely what I see SIAI as being about.
Hmmm. A mathematician learning a new field thinks for himself, up to a point. Oh, he gets his ideas, theorems, and even proofs from the book, but he is supposed to verify the thinking for himself.
The same kind of thing applies to scientists. They get ideas, formulas, and even empirical data from other scientists, but they are supposed to verify the inferences and even some of the derivations themselves. At least in their own field. A neuroscientist using FMRI doesn’t need to know the fine points of the portions of QED dealing with particle spins in a varying magnetic field. Nor the computer science involved in the image processing. But he does appreciate that these tools, whether he understands them in detail himself or not, are not based on tradition or authority, but instead draw their legitimacy from the work of his colleagues in those fields who definitely do think for themselves.
If the balance you seek to strike is the balance that lets you distinguish path-breaking innovation from crackpottery, I would suggest this: It is ok to try doing something that the experts think is impossible if you really understand why they are so pessimistic and you think you might understand why they are wrong.
I’m not sure that’s true. The issue isn’t what a person “thinks”...it’s what a person ultimately concludes. A scientist must think for itself in order to hypothesize, no?
I think science goes wrong when scientists conclude for themselves, in the face of the actul facts on the matter. I think what is being referenced above is how to separate information from who said it, and how.
Science works by scientists not doing all their thinking for themselves. That’s also how it fails. Getting the balance right may be hard, but no-one has really tried very hard, so it may not be. Trying to do that is largely what I see SIAI as being about.
Hmmm. A mathematician learning a new field thinks for himself, up to a point. Oh, he gets his ideas, theorems, and even proofs from the book, but he is supposed to verify the thinking for himself.
The same kind of thing applies to scientists. They get ideas, formulas, and even empirical data from other scientists, but they are supposed to verify the inferences and even some of the derivations themselves. At least in their own field. A neuroscientist using FMRI doesn’t need to know the fine points of the portions of QED dealing with particle spins in a varying magnetic field. Nor the computer science involved in the image processing. But he does appreciate that these tools, whether he understands them in detail himself or not, are not based on tradition or authority, but instead draw their legitimacy from the work of his colleagues in those fields who definitely do think for themselves.
If the balance you seek to strike is the balance that lets you distinguish path-breaking innovation from crackpottery, I would suggest this: It is ok to try doing something that the experts think is impossible if you really understand why they are so pessimistic and you think you might understand why they are wrong.
I’m not sure that’s true. The issue isn’t what a person “thinks”...it’s what a person ultimately concludes. A scientist must think for itself in order to hypothesize, no? I think science goes wrong when scientists conclude for themselves, in the face of the actul facts on the matter.
I think what is being referenced above is how to separate information from who said it, and how.