Online research in philosophy

According to the Carter-Leslie Doomsday Argument, we should assign a high probability to the hypothesis that the human species will go extinct very soon. The argument is based on the application of Bayes’s theo-rem and a certain indifference principle with respect to the temporal location of our observed birth rank within the totality of birth ranks of all humans who will ever have lived. According to Bostrom’s Simulation Argument, which appeals to a weaker indifference principle than the Doomsday Argument, at least one of the following three propositions must be true: (1) the human species is very likely to go extinct before reaching a posthuman stage, (2) it is very unlikely that some posthuman civili-zation will run a significant number of ancestor simula-tions, (3) it is almost sure that we are living in a com-puter simulation. According to my Doomsday Simulation Argument, both of the following propositions must be true: (1) it is almost sure that the human species will not go extinct before reaching a posthuman stage, (2) it is almost sure that we are not living in a computer simulation.

John Leslie's Doomsday argument uses the frequency interpretation of probability to argue that the end of the universe is closer than we might have thought. Oh well - all the worse for the frequency interpretation.

Carter and Leslie's Doomsday Argument maintains that reflection upon the number of humans born thus far, when that number is viewed as having been uniformly randomly selected from amongst all humans, past, present and future, leads to a dramatic rise in the probability of an early end to the human experiment. We examine the Bayesian structure of the Argument and find that the drama is largely due to its oversimplification.

The Carter-Leslie Doomsday argument, as standardly presented, relies on the assumption that you have knowledge of your approximate birth rank. I demonstrate that the Doomsday argument can still be given in a situation where you have no knowledge of your birth rank. This allows one to reply to Bostrom's defense of the Doomsday argument against the refutation based on the idea that your existence makes it more likely that many observers exist.

In a recent paper in this journal, Ken Olum attempts to refute the Doomsday argument by appealing to the self-indication assumption (SIA), the idea that your very existence gives you reason to think that there are many observers. In contrast to earlier refutation attempts that use this strategy, Olum confronts and try to counter some of the objections that have been made against SIA. We argue that his defense of SIA is unsuccessful. This does not, however, mean that one has to accept the Doomsday argument (or the other counterintuitive results that flow from related thought experiments). A developed theory of observation selection effects shows why the Doomsday argument is inconclusive and how one can consistently reject both it and SIA.

This paper attempts three tasks in relation to Carter and Leslie's Doomsday Argument. First, it criticises Timothy Chambers' 'Ussherian Corollary', a striking but unsuccessful objection to standard Doomsday arguments. Second, it reformulates the Ussherian Corollary as an objection to Bradley Monton's variant Doomsday and Nick Bostrom's Simulation Argument. Finally, it tries to diagnose the epistemic/metaphysical problems facing Doomsday-related arguments.1.

A refutation of the doomsday argument is offered. Through a simple thought experiment analysed in Bayesian terms the fallacy is shown to be the assumption that a currently living person represents a random sample from the population of all persons who will ever have existed. A more general version of the counter argument is then given. Previous arguments that purport to answer this concern are also addressed. One result is determining criteria for the applicability of time sampling arguments, i.e., under what conditions can a specific instant in time be regarded as a random sample from a time span. Given this new understanding, the incredible consequences of the doomsday and related arguments evaporate.

A refutation of the doomsday argument is offered. Through a simple thought experiment analysed in Bayesian terms the fallacy is shown to be the assumption that a currently living person represents a random sample from the population of all persons who will ever have existed. A more general version of the counter argument is then given. Previous arguments that purport to answer this concern are also addressed. One result is determining criteria for the applicability of time sampling arguments, i.e., under what conditions can a specific instant in time be regarded as a random sample from a time span. Given this new understanding, the incredible consequences of the doomsday and related arguments evaporate.

George Sowers tries to refute the Doomsday argument on grounds that true random sampling requires all possible samples to be equally probable the time when the sample is taken. Yet the Doomsday argument does not rely on true random sampling. It presupposes random sampling only in a metaphorical sense. After arguing that Sowers’ critique fails, I outline my own view on the matter, which is that the Doomsday argument is inconclusive and that by developing a theory of observation selection effects one can show why that is so.