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The paper's argument appears to be: 1) There is a fifty percent chance that the sort of word-simulations postulated by the simulation argument are not possible

The paper's argument appears to be: 1) There is a fifty percent chance that the sort of word-simulations postulated by the simulation argument are not possible, and thus we live in reality not a simulation. 2) Even if such simulations are possible, there is a small but non-zero chance that we still happen to live in base reality. By adding these two together, the paper concludes that we are slightly more likely to live in reality then a simulation. The author attempts to justify the 50% assumption on the basis of the principle of indifference.

winstonewert 6y ago
My assessment is that invoking the principle of indifference here is dubious. The appropriate priors are debatable, but we have lots of information on the plausibility of building world-simulations.
- mannykannot 6y ago
  I am equally skeptical of applying the principle of indifference here, and note that Bostrom also leans heavily on it in his original argument. In situations where we really have no good idea of what the odds are, the principle of indifference seems to implicitly assume more knowledge than we actually have, allowing us to cloak our speculation in an aura of unjustified quantifiability.
  - skissane 6y ago
    If you are going to use Bayesian probability, you need to assign a prior probability. And the principle of indifference is the simplest non-informative prior, so it makes sense as a default choice, unless one has some good reason to choose a different prior instead. Using a subjective Bayesian approach, in which Bayesian probabilities are just an expression of your own subjective judgement, you can choose priors on subjective personal grounds such as your intuition, whims, or desires (what you want to be true). By contrast, in objective Bayesianism, we need to provide some objective rational justification of the prior we choose, in which case it is hard to justify any initial prior for the simulation hypothesis than 0.5. Does it really "implicitly assume more knowledge than we actually have"? To assign an epistemic probability of 0.5 exactly to a proposition is to be in a state of zero knowledge concerning its truth. As our knowledge moves away from zero, epistemic probability moves away from 0.5 and closer to either 0.0 or 1.0. To assign an epistemic probability of 0.5 exactly is to assume no knowledge at all.
    - mannykannot 6y ago
      > Does it really "implicitly assume more knowledge than we actually have"? To assign an epistemic probability of 0.5 exactly to a proposition is to be in a state of zero knowledge concerning its truth? This seems to me to be a slightly burden-shifting way to look at the issue. If one is assignining a more-or-less precise value - whatever it is - one should have a more-or-less solid reason for using that value and not some other. > To assign an epistemic probability of 0.5 exactly is to assume no knowledge at all. When, for example, I assign a probability of 0.5 to a fair coin showing heads after being tossed, I am most definitely not assuming no knowledge at all. If, on the other hand, I were asked to assume a probability for a scafwich showing a flantex after being zenquexed, I would have no basis for saying 0.5, or any other value.
      - skissane 6y ago
        Are you talking about frequentist probability or epistemic/Bayesian probability? Your example of tossing a fair coin is potentially confusing in that, for that specific example, both approaches to probability can produce the same answer, which can promote the confusion of treating them interchangeably. If I have a coin which I don't know is fair, I can't assign a frequentist probability, but I can assign an objective Bayesian probability of 0.5, using either the principle of indifference or a uniform prior. Once I learn the coin is fair, I update the Bayesian probability, and it is still 0.5. Learning the fact that a coin is fair is not informative in terms of objective Bayesian probability, since it doesn't lead to any change in that probability. By contrast, learning that the coin is unfair is informative, and will lead to you updating to a different probability. > If, on the other hand, I were asked to assume a probability for a scafwich showing a flantex after being zenquexed, I would have no basis for saying 0.5. You have no basis to assign a frequentist probability. You do have a basis to assign an objective Bayesian probability of 0.5, the principle of indifference. And subjective Bayesian probabilities are subjective, so what subjective probability you assign is up to you.
        mannykannot 6y ago
        I think there is a a flip way to look at this and a more serious way. First the flip way: how much are you prepared to bet on the outcome of one hundred trials in which a scafwich is zenquexed? More seriously, as part of a process of Bayean updating, such as an experiment, the adoption of a starting position on the basis of the principle of indifference (or a uniform prior) is often a reasonable way to proceed, but in the case of both Bostrom's and Kipping's position on the simulation argument, no such process is performed, no empirical evidence is applied to the question, and the outcome is dominated by the prior, which, as you yourself seem to acknowledge, has no basis in current factual knowledge. There is an important difference between, on the one hand, the ignorance of not being able to know in advance the outcome of a specific instance of a stochastic process, as in the case of a coin toss, and on the other hand, the ignorance of not knowing anything about the process itself. > You do have a basis to assign an objective Bayesian probability of 0.5, the principle of indifference. This seems to me to be begging the question. > And subjective Bayesian probabilities are subjective, so what subjective probability you assign is up to you. Exactly - neither me, you nor anyone else has any objective reason to believe this value to be more accurate than any other, and invoking the principle of indifference in these circumstances does not alter that fact.

winstonewert 6y ago

My assessment is that invoking the principle of indifference here is dubious. The appropriate priors are debatable, but we have lots of information on the plausibility of building world-simulations.

mannykannot 6y ago
I am equally skeptical of applying the principle of indifference here, and note that Bostrom also leans heavily on it in his original argument. In situations where we really have no good idea of what the odds are, the principle of indifference seems to implicitly assume more knowledge than we actually have, allowing us to cloak our speculation in an aura of unjustified quantifiability.
- skissane 6y ago
  If you are going to use Bayesian probability, you need to assign a prior probability. And the principle of indifference is the simplest non-informative prior, so it makes sense as a default choice, unless one has some good reason to choose a different prior instead. Using a subjective Bayesian approach, in which Bayesian probabilities are just an expression of your own subjective judgement, you can choose priors on subjective personal grounds such as your intuition, whims, or desires (what you want to be true). By contrast, in objective Bayesianism, we need to provide some objective rational justification of the prior we choose, in which case it is hard to justify any initial prior for the simulation hypothesis than 0.5. Does it really "implicitly assume more knowledge than we actually have"? To assign an epistemic probability of 0.5 exactly to a proposition is to be in a state of zero knowledge concerning its truth. As our knowledge moves away from zero, epistemic probability moves away from 0.5 and closer to either 0.0 or 1.0. To assign an epistemic probability of 0.5 exactly is to assume no knowledge at all.
  - mannykannot 6y ago
    > Does it really "implicitly assume more knowledge than we actually have"? To assign an epistemic probability of 0.5 exactly to a proposition is to be in a state of zero knowledge concerning its truth? This seems to me to be a slightly burden-shifting way to look at the issue. If one is assignining a more-or-less precise value - whatever it is - one should have a more-or-less solid reason for using that value and not some other. > To assign an epistemic probability of 0.5 exactly is to assume no knowledge at all. When, for example, I assign a probability of 0.5 to a fair coin showing heads after being tossed, I am most definitely not assuming no knowledge at all. If, on the other hand, I were asked to assume a probability for a scafwich showing a flantex after being zenquexed, I would have no basis for saying 0.5, or any other value.
    - skissane 6y ago
      Are you talking about frequentist probability or epistemic/Bayesian probability? Your example of tossing a fair coin is potentially confusing in that, for that specific example, both approaches to probability can produce the same answer, which can promote the confusion of treating them interchangeably. If I have a coin which I don't know is fair, I can't assign a frequentist probability, but I can assign an objective Bayesian probability of 0.5, using either the principle of indifference or a uniform prior. Once I learn the coin is fair, I update the Bayesian probability, and it is still 0.5. Learning the fact that a coin is fair is not informative in terms of objective Bayesian probability, since it doesn't lead to any change in that probability. By contrast, learning that the coin is unfair is informative, and will lead to you updating to a different probability. > If, on the other hand, I were asked to assume a probability for a scafwich showing a flantex after being zenquexed, I would have no basis for saying 0.5. You have no basis to assign a frequentist probability. You do have a basis to assign an objective Bayesian probability of 0.5, the principle of indifference. And subjective Bayesian probabilities are subjective, so what subjective probability you assign is up to you.
      - mannykannot 6y ago
        I think there is a a flip way to look at this and a more serious way. First the flip way: how much are you prepared to bet on the outcome of one hundred trials in which a scafwich is zenquexed? More seriously, as part of a process of Bayean updating, such as an experiment, the adoption of a starting position on the basis of the principle of indifference (or a uniform prior) is often a reasonable way to proceed, but in the case of both Bostrom's and Kipping's position on the simulation argument, no such process is performed, no empirical evidence is applied to the question, and the outcome is dominated by the prior, which, as you yourself seem to acknowledge, has no basis in current factual knowledge. There is an important difference between, on the one hand, the ignorance of not being able to know in advance the outcome of a specific instance of a stochastic process, as in the case of a coin toss, and on the other hand, the ignorance of not knowing anything about the process itself. > You do have a basis to assign an objective Bayesian probability of 0.5, the principle of indifference. This seems to me to be begging the question. > And subjective Bayesian probabilities are subjective, so what subjective probability you assign is up to you. Exactly - neither me, you nor anyone else has any objective reason to believe this value to be more accurate than any other, and invoking the principle of indifference in these circumstances does not alter that fact.