If you want to discuss or debate an issue to resolution/conclusion with me, explicitly ask for that. I’m open, by request, to putting major effort into resolving disagreements.
curi
Did you read the context? Someone asked the Popperian view on giving a probability of future weather. So I answered that. What exactly do you think the context is?
-7.65% of your income into Social Security good luck getting that back
This is incorrect. The actual sociality security rate is DOUBLE that. Half is paid by the employer & half by employee to make it look smaller. That half you don’t see does count b/c it lowers salaries offered.
Also you included medicare taxes in the figure. social security alone is less.
Also it’s a % of your income up to something like 110k, income above the limit has 0 payroll taxes.
Yudkowsky hasn’t read Popper or wasn’t paying attention. Popper’s didn’t advocate that position; it’s a myth which Popper repeatedly denied. See e.g. “The Popper Legend” section in Popper’s replies to his critics in the Schilpp book.
Who do you think advanced CR? I think only David Deutsch has improved on Popper.
FYI that is a misleading statement of Critical Rationalism.
For one thing, Popper was not a “belief philosopher” so he wouldn’t have stated it quite like that.
There are a lot of misleading statements about CR floating around. Most come from its opponents trying to make sense of it on their own terms. In trying to formulate it in a way that makes sense given their anti-CR premises, they change it. It’s best to read primary sources for this.
You haven’t understood which part is the myth I was talking about or read the source I gave.
You’ve now given a short statement of the conclusion of an argument Popper made in LScD (but not the argument itself, and also missing too much detail to even understand his point). It is a purely logical argument and unexceptionable. The Gardner passage doesn’t address it at all, nor make any argument, but merely asserts.
Please do your homework instead of just googling out of context snippets. You don’t know what the Popper legend is, nor what Popper’s argument for the quoted conclusion you pasted is.
Which Miller publication or argument?
I wonder what they think of the discussion of the Oracle in The Fabric of Reality, ch1.
Deutsch does say what makes an explanation good. He has a TED talk about it, and a new book, The Beginning of Infinity (came out 2 days ago in the UK) which has this as a major theme. Good explanations are hard to change while they still solve the same problem. The book has examples and elaboration.
You have to actually read Popper’s books to understand what he means. You are taking short summaries of conclusions without understanding Popper’s arguments behind them.
For example, when Popper says “theory” there he does not mean any theory. He means a universal theory. This is the kind of thing one finds out by reading him.
Popper gave an argument in LScD along these lines:
Consider a theory, T, that all swans are white. T is a universal theory.
No confirming evidence can prove T is true. You can see 5 white swans or 500 or 50 million. Still might be false.
But if you see one black swan it is false.
This is an asymmetry between confirmation and falsification when applied to universal theories. It does not hold for all theories.
Consider the negation ~T. At least one swan is not white. This theory cannot be refuted by any amount of observations. But it can be confirmed with only one observation. ~T is a non-universal theory and not the kind science is after.
Is he wrong? This is pure logic. Popper in LScD was interest in scientific laws—that is, universal theories—and in that context he was unobjectionably correct about confirmation and falsification.
What you are doing is taking short quotes and imagining the context isn’t relevant, and that they only have one possible meaning. That is an unscholarly beginner’s mistake.
I’ve simplified various things here (for example Popper’s approach is not falsificationism; saying it is is a myth; linking to a page titled Falsifiability and calling it a refutation of Popper demonstrates your ignorance; and I ignored the duhem-quine problem which Popper did address from the start). And Popper had more and better arguments later. But you get the idea?
That is the duhem-quine problem. Popper addresses it in his book as I said.
Part of the answer is: Popper is a fallibilist. Of course our knowledge isn’t certain.
However, uncertain does not mean probabilistic. Probabilistic is not the only option.
I wonder: how do you figure out the probability that you went temporarily insane?
And whatever you say, how do you figure out the probability that you were right about that? etc
I think assigning probabilities leads to a regress.
Popper did not argue that that confirmation and falsification have fundamentally different rules. They both obey the rules of logic.
Confirmation cannot be any evidence for universal theories. None, probabilistic or otherwise. Popper explained this and did the math. If you disagree people provide the math that governs it and explain how it works.
As to the rest you’re asking how Popper deals with fallible evidence. If you would read his books you could find the answer. He does have an answer, not none, and it isn’t probabilistic.
Let me ask you: how do you deal with the regress I asked Manfred about?
It says “When we see evidence, hypotheses that assigned a higher likelihood to that evidence, gain probability at the expense of hypotheses that assigned a lower likelihood to the evidence.”
This does not work. There are infinitely many possible hypotheses which assign a 100% probability to any given piece of evidence. So we can’t get anywhere like this. The probability of each remains infinitesimal.
I don’t want to argue terminology but the Duhem-Quine problem is about the problem of the fallibility of evidence, which is the problem you raised. Which is what Wikipedia says. You were talking about altering background assumptions our evidence relies on with e.g. the temporary insanity.
You raise the issue of giving up. But that’s not the alternative. It’s not this or nothing. Popper has an epistemology without a regress.
You say the signs keep flipping, and the doubts keep getting smaller. But do they really get smaller? If I were to play along and try to estimate the chance of temporary insanity I’d put it very low, say 0.00001%. And if I were to estimate the chance that I had that figure substantially incorrect, I’d put it very high, say 50%. And if I were to try to estimate the chance I was right about the 50% -- well beats me so I’ll have to say 5% or something. And the chance I was right about that 5%? Ugh. It’s low. I think I’m wrong by now.
Note: I don’t think those issues are matters of probability. Please don’t attribute that to me later. I was just trying to play along with your theory to discuss it.
I don’t think the sign flipping argument works either. The original probability depends on its probabilistic justification being correct, which depends on its probabilistic justification being correct, and so on. Break the chain and the whole thing falls apart. I’m guessing you have some extra premise about margins or error or something, so you expect if one thing is wrong the stuff it depends on only changes slightly. But what is the probability you are right about that? You face another regress on that issue. And whatever other arguments and premises and anything else you bring up, you’re simply going to face still more regresses as I question them.
EDIT PS: Thanks for the philosophy of encyclopedia link. It says Duhem-Quine was invented in the 1950s. Popper addressed the issue before that. I thought he might have invented it before them but wasn’t sure about the dates.
The regress doesn’t offer any probability at all because it never ends and you cannot analyze the whole thing which would require infinitely many steps. You imply it has a simple pattern but I don’t think it does as my example showed (where I tried to estimate probabilities successively) which you did not reply to.
If you could analyze the whole infinite regress, the probability it would offer that your first probability estimate was correct is infinitesimal because if you consider the odds of infinitely many probabilities—all below 1 -- you get an infinitesimal result. (If you have 99%, and then 99% of that, and so on, it keeps going down forever).
As I commented on, it does not alternate. Let me try again:
Theory T1 is the temporary insanity theory. You assign it 1%.
Theory T2 is the theory that your first probability assignment was correct. You assign that 90%.
Now, suppose we find out T2 is false. What happens? Does the probability of T1 go up or down?
We don’t know (given only the statements made so far; if you introduce new statements you could come up with an answer but they would themselves be subject to further questioning). So it isn’t true that the signs keep alternating and balance out. The answer is unknown, not stable. They don’t have signs at all.
The issue has nothing to do with “a lot of numbers”. Infinities are different than lots of numbers. They have special properties.
Thanks I ordered them. I’d only read individual articles of his.
The point is that you can’t and don’t know the probability of anything.
Whenever you make a guess at a probability (e.g. 0.1% chance of temporary insanity yesterday), you have to wonder (in your epistemology): what is the probability that this guess (this probability estimate) is correct?
And whatever you guess about that, you have to wonder it again. And then again.
None of this has to do with the imprecision of knowledge. How do you know you are in the right ballpark? How do you know that you are within plus or minus 50%? You do not know. You can say you are, and you can give that a probability. But that itself could be false, its probability could be questioned.
So there is a regress.
At any step in the regress, if you are mistaken, the whole thing crumbles, all the way to the very first probability you assigned. They don’t crumble a little with the addition of minor error, they simply could be anything whatsoever and you don’t know.
Why? Well Suppose you think the probability you were correct about T4 is 99%. And let’s suppose even that you’re right about that. It doesn’t matter. But it’s a 1% case. It could be T40 just as well, or T4000, and the probability could be 99.999%. It doesn’t matter.
So, T4 says that the probability you are correct about T3′s probability estimate is 99%. Which is true, but you’re unlucky this time. T4 is false.
Where does that leave T3? It leaves it unknown. Your probability estimate for it is not changed but gone entirely. You haven’t got one and you don’t know what it is. And with no status for T3, no reliability, no justification, no nothing, then T2 is gone too. And so goes T1. And T0. The end.
T3 said you’re 99% confident that T2′s probability estimate is correct. T2 said you’re 99% confident that T1′s probability estimate is correct. You see how they all fall apart? Each one depends on the next.
There are various ways out. You can make a probability estimate, and when asked the probability you are right about that, answer 100% or refuse to answer. You can suggest we stop asking. You can accept some things which haven’t got a probability (but this contradicts your general method). Whatever. But there is no rational solution which makes everything work. I think you may have misunderstood the regress as having something to do with the probability of the initial theory at each step (so that it goes up and down, in smaller and smaller amounts, and with opposite signs at each step). But that’s not it. It’s more meta than that. Every step is to ask the probability of the previous probability estimate (not theory directly about the real world).
You say we’re stuck with reality. This is true. But it does not mean that your picture of reality is correct. Popper has an epistemology which is not broken, which has no regress. This one is broken. There’s no need to despair, only to change your mind. To let your theories die in your place, as Popper put it.
ditto “bread nourishes” and one other famous example i forgot.
Actually you still do… You simply have to ask: what is the probability that the universal prior idea is correct? And whatever you say, ask the probability that is correct. And so on.
The regress works no matter what you say, even if you say something about universal priors.
Events have probabilities. Theories don’t. Given some theory of meteorology, you can predict the probability it will snow in Feb. But you can’t say the probability that that theory of meteorology is true.