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Bayesian update from sensationalistic sources

by houkime
11th May 2023
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Let's say we have statement X that we ascribe a prior probability of 0.3

Then let's say we have a news source N, presented as an infinite feed of statements.
N is sensationalistic with regards of X that are interesting to N:

  • If X is true N virtually always says that X is true.
  • But if X is not true N might still say that it is true.
  • N only reports if it intends to say that X is true, otherwise it says nothing and covers other topics instead.

The probability of N saying X is true when X is not true for our particular X is not known, but historically we know that N is wrong about 70% of times.

X is interesting to N and N says X is true.
How will this shift our belief in X?