Open thread, October 2011

MarkusRamikin

This thread is for discussing anything that doesn't seem to deserve its own post.

If the resulting discussion becomes impractical to continue here, it means the topic is a promising candidate for its own thread.

This thread is for discussing anything that doesn't seem to deserve its own post.

If the resulting discussion becomes impractical to continue here, it means the topic is a promising candidate for its own thread.

I estimate, that a currently working and growing superintelligence has a probability in a range of 1/million to 1/1000. I am at least 50% confident that it is so.

The probability is already just an expression of your own uncertainty. Giving a confidence interval over the probability does not make sense.

I agree. Perhaps he means to say that his opinion is based on very little evidence and is "just a hunch".

I do think that in fitting a model to data, you can give meaningful confidence intervals for parameters of those models which correspond to probabilities (e.g. p(heads) for a particular coin flipping device). But that's not relevant here.

1bentarm15y

I basically agree that the part of the original comment that you quote doesn't make any sense at all, and am not attempting to come to the defence of confidence intervals over probabilities, but it does feel like there should be some way of giving statements of probability and indicating how sure one is about the statement at the same time. I think, in some sense, I want to be able to say how likely I think it is that I will get new information that will cause me to update away from my current estimate, or give a second-derivative of my uncertainty, if you will. Let's say we have two bags, one contains 1 million normal coins, one contains 500,000 2-headed coins and 500,000 2-tailed coins. Now, I draw a coin from the first bag and toss it - I have a 50% chance of getting a head. I draw a coin from the second bag and toss it - I also have a 50% chance of getting a head, but it does feel like there's some meaningful difference between the two situations. I will admit, though, that I have basically no idea how to formalise this - I assume somebody, somewhere, does.

7Vaniver15y

It sounds to me like he is describing his distribution over probabilities, and estimates at least 50% of the mass of his distribution is between 1/1,000 and 1/1,000,000. Is that a convenient way to store or deal with probabilities? Not really, no, but I can see why someone would pick it.