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Self-Indication Assumption — LessWrong

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The self-indication assumption (SIA)1, a philosophical principle defined by Nick Bostrom2, one of the two major schools of anthropic probability (the other being the self-sampling assumption (SSA)), states that: SIA: All other things equal, an observer should reason as if they are randomly selected from the set of all possible observers. Note that "randomly selected" is weighted by the probability of the observers existing: under SIA you are still unlikely to be an unlikely observer, unless there are a lot of them. For instance, if there is a coin flip that on heads will create one observer, while on tails they will create two, then we have three possible observers (1st observer on heads, 1st on tails, 2nd on tails), each existing with probability 0.5, so SIA assigns 1/3 probability to each. Alternately, this could be interpreted as saying there are two possible observer (1st observer, 2nd observer on tails), the first existing with probability one and the second existing with probabil

x Self-Indication Assumption — LessWrong Self-Indication Assumption Edited by Jake Miller , et al. last updated 6th Sep 2014 The self-indication assumption (SIA) 1 , a philosophical principle defined by Nick Bostrom 2 , one of the two major schools of anthropic probability (the other being the self-sampling assumption (SSA)), states that: SIA : All other things equal, an observer should reason as if they are randomly selected from the set of all possible observers. Note that "randomly selected" is weighted by the probability of the observers existing: under SIA you are still unlikely to be an

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