Large groups of smart people are frequently wrong about the future, and overwhelmingly so about the non-immediate future. 0.1% may be low but it’s not ridiculously so.
(Also “they’re right and you’re wrong” is redundant. This has nothing to do with any set of scenario probabilities being “right”. And any debate of “p=.9” “no, p=.1″ is essentially silly because it misunderstands both the meaning of probability as a function of knowledge and our ability to create models which give meaningfully-accurate probabilities.)
And any debate of “p=.9” “no, p=.1″ is essentially silly because it misunderstands both the meaning of probability as a function of knowledge and our ability to create models which give meaningfully-accurate probabilities.
Subjective probability is (in particular) a tool for elicitation of model parameters from expert human gut-feelings, which you can then use to find further probabilities and align them with other gut-feelings and decisions, gaining precision from redundancy and removing inconsistencies. The subjective probabilities don’t promise to immediately align with physical frequencies, even where the notion makes sense.
It is a well-studied and useful process, you’d need a substantially more constructive reference than “it’s silly” (or you could just seek a reasonable interpretation).
Do you have a link for a top-level post that puts this kind of caveat on probability assignments? Personally, I think that if most people here understood it that way, they’d use more qualified language when talking about subjective probability. I also think that developing and standardizing such qualified language would be a useful project.
It is the sense in which the term “probability” is generally understood on OB/LW, with varying levels of comprehension by specific individuals. There are many posts on probability, both as an imprecise tool and an ideal (but subjective) construction. They should probably be organized in the Bayesian probability article on the wiki. In the meantime, you are welcome to look for references in the Overcoming Bias archives.
Large groups of smart people are frequently wrong about the future, and overwhelmingly so about the non-immediate future. 0.1% may be low but it’s not ridiculously so.
(Also “they’re right and you’re wrong” is redundant. This has nothing to do with any set of scenario probabilities being “right”. And any debate of “p=.9” “no, p=.1″ is essentially silly because it misunderstands both the meaning of probability as a function of knowledge and our ability to create models which give meaningfully-accurate probabilities.)
Subjective probability is (in particular) a tool for elicitation of model parameters from expert human gut-feelings, which you can then use to find further probabilities and align them with other gut-feelings and decisions, gaining precision from redundancy and removing inconsistencies. The subjective probabilities don’t promise to immediately align with physical frequencies, even where the notion makes sense.
It is a well-studied and useful process, you’d need a substantially more constructive reference than “it’s silly” (or you could just seek a reasonable interpretation).
As you explain it, it’s not silly.
Do you have a link for a top-level post that puts this kind of caveat on probability assignments? Personally, I think that if most people here understood it that way, they’d use more qualified language when talking about subjective probability. I also think that developing and standardizing such qualified language would be a useful project.
It is the sense in which the term “probability” is generally understood on OB/LW, with varying levels of comprehension by specific individuals. There are many posts on probability, both as an imprecise tool and an ideal (but subjective) construction. They should probably be organized in the Bayesian probability article on the wiki. In the meantime, you are welcome to look for references in the Overcoming Bias archives.
You may be interested in the following two posts, related to this discussion:
Probability is in the Mind
When (Not) To Use Probabilities