Human beings are universal knowledge creators: they can create any knowledge
that any other knowledge creator can create.
For interesting definitions of ‘can’, perhaps. I know some humans who can’t create
much of anything.
All human beings create knowledge—masses of it. Certain ideas can and do impair a person’s creativity, but it is always possible to learn and to change one’s ideas.
The only known tenable way of creating knowledge is by conjectures and refutations.
I’m not sure that counts as a ‘way of creating knowledge’. ‘Conjectures’ sounds to me
like a black box which would itself contain the relevant bit.
It’s not just conjectures, it’s “conjectures and refutations”. Knowledge is created by advancing conjectural explanations to solve a problem and then criticizing those conjectures in an attempt to refute them. The goal is to find a conjecture that can withstand all criticisms we can think of and to refute all rival conjectures.
Induction is a myth.
I’d want to know what you mean by ‘myth’. It’s worked so far, though that only counts
as evidence for those of us blinded by the veil of Maya.
No, it never worked. Not a bit. That’s what I mean by myth.
Theories are either true or false: there is no such thing as the probability that a
theory is true.
Confirmation does not make a theory more likely or better supported—the only role
of confirmation is to provide a ready stock of criticisms of rival theories.
Probability is in the mind. Theories are either true or false, and there is such a thing
as the probability that a theory is true.
Theories are objective. Whether you think a theory is true or false has no bearing on whether it is in fact true or false. Moreover, how do you assign a probability to a complex real-world theory like, say, multiversal quantum mechanics? What counts is whether the theory has stood up to criticism as an explanation to a problem or set of problems. If it has, who cares about how probable you think it is? It’s not the probability that you should care about, it’s the explanation.
The most important knowledge is explanations.
I’m not sure what you mean by that.
Above all else, we should try to find explanations for things; explanations are the most important kind of knowledge.
There is no route to certain knowledge: we are all fallible.
This shows the remarks about ‘probability’ above to be merely a definitional dispute.
Probability describes uncertainty, and you admit that we have uncertain knowledge.
Knowledge is always uncertain, yes, but it is impossible to objectively quantify the uncertainty. Put another way, you cannot know what you do not yet know. Theories can be wrong in all sorts of ways but you have no way of doing in advance how or if a theory will go wrong. It’s not a definitional dispute.
We don’t need certain knowledge to progress: tentative, fallible, knowledge is just
fine.
All human beings create knowledge—masses of it. Certain ideas can and do impair a person’s creativity, but it is always possible to learn and to change one’s ideas.
It’s not just conjectures, it’s “conjectures and refutations”. Knowledge is created by advancing conjectural explanations to solve a problem and then criticizing those conjectures in an attempt to refute them. The goal is to find a conjecture that can withstand all criticisms we can think of and to refute all rival conjectures.
No, it never worked. Not a bit. That’s what I mean by myth.
Theories are objective. Whether you think a theory is true or false has no bearing on whether it is in fact true or false. Moreover, how do you assign a probability to a complex real-world theory like, say, multiversal quantum mechanics? What counts is whether the theory has stood up to criticism as an explanation to a problem or set of problems. If it has, who cares about how probable you think it is? It’s not the probability that you should care about, it’s the explanation.
Above all else, we should try to find explanations for things; explanations are the most important kind of knowledge.
Knowledge is always uncertain, yes, but it is impossible to objectively quantify the uncertainty. Put another way, you cannot know what you do not yet know. Theories can be wrong in all sorts of ways but you have no way of doing in advance how or if a theory will go wrong. It’s not a definitional dispute.
OK, we agree on that!
Probability is subjectively objective. All conjectures/models are wrong, but some are useful to the extent that they successfully constrain expected experience.