A well-known proof by Alonzo Church, first published in 1963 by Frederic Fitch, purports to show that all truths are knowable only if all truths are known. This is the Paradox of Knowability. If we take it, quite plausibly, that we are not omniscient, the proof appears to undermine metaphysical doctrines committed to the knowability of truth, such as semantic anti-realism. Since its rediscovery by Hart and McGinn (1976), many solutions to the paradox have been offered. In this article, we (...) present a new proof to the effect that not all truths are knowable, which rests on different assumptions from those of the original argument published by Fitch. We highlight the general form of the knowability paradoxes, and argue that anti-realists who favour either an hierarchical or an intuitionistic approach to the Paradox of Knowability are confronted with a dilemma: they must either give up anti-realism or opt for a highly controversial interpretation of the principle that every truth is knowable. (shrink)

In recent years, anthropic reasoning has been used to justify a number of controversial skeptical hypotheses. In this paper, we consider two prominent examples, viz. Bostrom’s ‘Simulation Argument’ and the problem of ‘Boltzmann Brains’ in big bang cosmology. We argue that these cases call into question the assumption, central to Bayesian confirmation theory, that the relation of evidential confirmation is universally symmetric. We go on to argue that the fact that these arguments appear to contradict this fundamental assumption should not (...) be taken as an immediate refutation, but should rather be seen as indicative of the peculiar role that the relevant hypotheses play in their respective epistemic frameworks. (shrink)

Anthony Brueckner, in a recent article, proffers ‘a new way of thinking about Bostrom's Simulation Argument’ . His comments, however, misconstrue the argument; and some words of explanation are in order.The Simulation Argument purports to show, given some plausible assumptions, that at least one of three propositions is true . Roughly stated, these propositions are: almost all civilizations at our current level of development go extinct before reaching technological maturity; there is a strong convergence among technologically mature civilizations such that (...) almost all of them lose interest in creating ancestor-simulations; almost all people with our sorts of experiences live in computer simulations. I also argue that conditional on you should assign a very high credence to the proposition that you live in a computer simulation. However, pace Brueckner, I do not argue that we should believe that we are in simulation. 1 In fact, I believe that we are probably not simulated. The Simulation Argument purports to show only that, as well as , at least one of – is true; but it does not tell us which one.Brueckner also writes: " It is worth noting that one reason why Bostrom thinks that the number of Sims [computer-generated minds with experiences similar to those typical of normal, embodied humans living in a Sim-free early 21 st century world] will vastly outstrip the number of humans is that Sims ‘will run their … ". (shrink)

This article reports on a newly discovered bug in the original simulation argument. Two different ways of patching the argument are proposed, each of which preserves the original conclusion.

N. Bostrom’s simulation argument and two additional assumptions imply that we likely live in a computer simulation. The argument is based upon the following assumption about the workings of realistic brain simulations: The hardware of a computer on which a brain simulation is run bears a close analogy to the brain itself. To inquire whether this is so, I analyze how computer simulations trace processes in their targets. I describe simulations as fictional, mathematical, pictorial, and material models. Even though the (...) computer hardware does provide a material model of the target, this does not suffice to underwrite the simulation argument because the ways in which parts of the computer hardware interact during simulations do not resemble the ways in which neurons interact in the brain. Further, there are computer simulations of all kinds of systems, and it would be unreasonable to infer that some computers display consciousness just because they simulate brains rather than, say, galaxies. (shrink)

Nick Bostrom has famously defended the credibility of the simulation hypothesis – the hypothesis that we live in a computer simulation. Barry Dainton has recently employed the simulation hypothesis to defend the ‘simulation solution’ to the problem of natural evil. The simulation solution claims that apparently natural evils are in fact the result of wrong actions on the part of the people who create our simulation. In this way, it treats apparently natural evils as actually being moral evils, allowing them (...) to be explained via the free will theodicy. Other theodicies which assimilate apparently natural evils to moral ones include Fall theodicies, which attribute apparently natural evils to the biblical Fall, and diabolical theodicies, which attribute them to the activity of demons. Unfortunately, Dainton fails to give compelling reasons for preferring the simulation solution to Fall or diabolical theodicies. He gives one argument against diabolical theodicies, but it has no force against their best version, and he does not discuss Fall theodicies at all. In this article, I attempt to rectify this. I discuss several problems faced by Fall and diabolical theodicies which the simulation solution avoids. These provide some reason to prefer the simulation solution to these alternatives. (shrink)

Both patched versions of the Bostrom/Kulczycki simulation argument contain serious objective errors, discovered while attempting to formalize them in predicate logic. The English glosses of both versions involve badly misleading meanings of vague magnitude terms, which their impressiveness benefits from. We fix the errors, prove optimal versions of the arguments, and argue that both are much less impressive than they originally appeared. Finally, we provide a guide for readers to evaluate the simulation argument for themselves, using well-justified settings of the (...) argument parameters that have simple, accurate statements in English, which are easier to understand and critique than the statements in the original paper. (shrink)