[ExI] Conspiracy epistemology (Was: cut off worried)

[William Flynn Wallace]

We should have a way of dealing with those cases where foul play is un
likely but possible.
We might estimate perhaps 10 percent chance Scalia was slain, ja?

On the basis of no evidence at all?  This is very far from scientific thinking.

bill w


On Thu, Feb 18, 2016 at 5:28 PM, Anders Sandberg <anders at aleph.se> wrote:

> On 2016-02-18 15:35, spike wrote:
>
> ... By the way, does anybody have a good long-term database of historical
> assassinations?
>
> --
> Anders
>
> We should have a way of dealing with those cases where foul play is un likely but possible.  We might estimate perhaps 10 percent chance Scalia was slain, ja?
>
>
> Actually, way lower. Think of it like this: the murder rate of the US is
> about 4 per 100,000, or a probability of 0.00004.
>
> There are no doubt some murders that are successfully hidden as natural;
> if we assume for every discovered murder there is a hidden one we are
> likely extremely paranoid, but that brings up the probability to 0.00008.
>
> Now, assassinations are actually fairly rare: most murder is of
> non-prominent persons. Even there, judges are uncommon (in the data in Snitch,
> T. H. (1982). Terrorism and political assassinations: A transnational
> assessment, 1968-80. *The Annals of the American Academy of Political and
> Social Science*, 463(1), 54-68. only 3% of successful assassinations
> involved judges). So thinking a particular judge's death is due to foul
> play without any supporting evidence should lower the probability of the
> statement being true by quite a lot - a very rough assassination rate
> (assassinations/deaths) I estimated using Wikipedia statistics is 7.8e-4. A
> lot of those deaths were murders, so let's be charitable and say a factor
> of 1e-3. That makes a probability of 8e-8.
>
> So, the ultra-paranoid prior for Scalia being assassinated is a
> probability of 8e-8.
>
> Now, if you started to get positive evidence that prior would be
> multiplied by Bayes factors of the form
> P(evidence|assassination)/(P(evidence|assassination)P(assassination) +
> P(evidence|no assassination)P(no assassination), which is roughly, since
> assassinations are rare, P(evidence|assassination)/P(evidence|no
> assassination). For example, lack of autopsy is pretty likely in either
> case, so the Bayes factor is only slightly larger than 1. Seeing ninjas
> disappear from the scene produces a big factor, since they rarely show up
> when people die for non-assassination reasons. Not seeing ninjas (because
> maybe they are invisible like all really good ninjas!) produces a Bayes
> factor of 1: you would expect that in either case.
>
> So, can anybody scrounge up enough Bayes factors to get the prior up to
> 0.1?
>
> --
> Anders Sandberg
> Future of Humanity Institute
> Oxford Martin School
> Oxford University
>
>
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