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Jiro comments on Using Bayes to dismiss fringe phenomena - Less Wrong Discussion
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Generally, the hard to detect effects that those scientists research are not ones which
-- have been enthusiastically promoted by nonscientists
-- conflict with basic scientific principles that are well-studied and well-understood (often the proponents don't even understand that what they are suggesting conflicts with such principles)
-- have been well-studied themselves and already found to be false
Given the Fermi paradox the existence of aliens doesn't violate scientific principles. Yet aliens are outside of what you can study scientifically.
When it comes to that class we don't really talk about judging them "prior to empirical investigation".
It looks like it. It's about status.
No, it's a Bayseian update based on "the probability that something is true, conditional on being enthusiastically promoted by nonscientists and rejected or ignored by scientists, is really really low". That's what you use Bayseian updates for. Science works; it may not do so with complete certainty, but the odds heavily favor it.
It's no more about status than wanting to go to a medical doctor instead of a faith healer is about status.
A lot of things get ignored by scientists because you don't get funding for studying the topic. Xrisk would be a good example. FHI finds it hard to raise money via the traditional way for the subject.
It works through empirical investigation. It doesn't do much prior to empirical investigation.
As a heuristic, I suspect ignoring things ignored by most scientists will actually work pretty well for you. Its not an unreasonable assumption to say that "given no other information, the majority of scientists dismissing a subject lowers my probability that that subject has any grounding". Thats a sensible thing to do, and does indeed use a simple Bayesian logic.
Note that we essentially do this for all science, in that we tend to accept the scientific consensus. We can't be subject specialists in everything, so while we can do a bit of reading, its probably fine to just think: what most scientists think is probably the closest to correct I am capable of being without further study.
If you don't have any information then that might be true. Usually you however do have some information.
That's only true for fields that are studied enough for there to be an evidence based scientific consensus.
There is an interesting exception -- if you are scientist yourself.
Bayseian calculation doesn't work on "a lot", it works on the odds, and the odds are much lower for such things.
As a prequel to wiring my article, I looked into studies of UAPs. None of these studies concluded that all investigated UAP's turns out to be either known phenomena, or solely unidentifiable due to insufficient observation data. All studies show that a minor percentage of UAPs resist identification (between 5 and 20 percent).
Thus we cannot say that we currently have a scientific understanding of all aerial phenomena.
When this is combined with Fermi's paradox, how come we don't conclude that we should study them some more?
If there's any inaccuracy in the reporting, any mundane event can "resist identification". Eyewitnesses are not as accurate as most people think they are.
And while you claim that ones that have insufficient observation data were excluded, I'll believe it when I see a study, because that can mean a lot of things. (If there is enough information to rule out causes X and Y, but not Z or A, is that 'insufficient observation data'? What if they ruled out all sorts of causes but didn't rule out the possibility of, say, a hoax?)
I applaud looking at the studies. I included references to 7 studies and 4 case collections (including one collection solely of radar backed observations) in the References section of my article:
http://myinnerouterworldsimulator.neocities.org/index.html
P(A | B) is not equal to 1 - p(A | not B). You are thinking p(A | B) = 1 - p(not A | B). Example:
p(A=0,B=0) = 0.1, p(A=0,B=1) = 0.2, p(A=1,B=0) = 0.3, p(A=1,B=1) = 0.4.
p(A=0 | B=0) = p(A=0,B=0) / ( p(A=1,B=0) + p(A=0,B=0) ) = 0.1 / (0.3+0.1) = 0.1/0.4 = 1/4
p(A=0 | B=1) = p(A=0,B=1) / ( p(A=0,B=1) + p(A=1,B=1) ) = 0.2 / (0.2+0.4) = 0.2/0.6 = 2/6 = 1/3
1/4 is not 1 - 1/3.
Someone else pointed this out already, are you updating on basic math errors?
I am aware of the error and will correct it - it's on my todo list :)
[EDIT] fixed! (hopefully!)
http://myinnerouterworldsimulator.neocities.org/
Hint: what happened to UFO sightings once everyone started to carry a high-resolution camera (in a smartphone) with them at all times?
Did you investigate what happened?
What happened is that UFO sightings basically disappeared. Turns out it's much harder to talk about seeing UFOs when you can't answer the question "So, why didn't you take a picture with your phone?"
references?
[edit]: This graph shows the frequency of reported UFO sightings inn Canada over the last 25 years. There is a steady increase in sightings over the years:
http://www.canadianuforeport.com/survey/images/ttlreports2013.gif
The graph originates from this survey: http://survey.canadianuforeport.com/
conducted by the Canadian astronomer Chris A. Rutkowski and non-astronomer Geoff Dittman
Hmm, interesting. Looks like I was wrong.