Alvin Plantinga’s evolutionary argument against naturalism (EAAN) claims that if both naturalism (N) and evolutionary theory (E) are true, then all our beliefs are unreliable (premiss 1). Consequently, given N&E, the belief in N&E is unreliable (premiss 2) and N&E is self-defeating (conclusion). The empirical verification argument against naturalism (EVAAN) is more cautious and improves EAAN by withstanding a rejoinder of the evolutionary naturalist to premiss 1. EVAAN claims that non-abstract beliefs that are not empirically verifiable are unreliable, given N&E (...) (premiss 1a). This anticipates the evolutionary naturalist’s claim that empirical verifications play a crucial role in peer assessments and sexual selection of intelligence, and that, therefore, N&E makes empirically verifiable beliefs often reliable (premiss-1 rejoinder). However, even then it can be argued that the belief in N&E is unreliable, given N&E (premiss 2), because N&E is neither abstract, nor empirically verifiable (premiss 1b). EVAAN distinguishes reliably verifiable intelligence from metaphysical intelligence and claims that, if N&E is true, humans are lacking metaphysical intelligence. This paper also contains an argument against EAAN, by supporting the premiss-1 rejoinder. (shrink)

This chapter explores global debunking arguments, debunking arguments that aim to give one a global defeater. I defend Alvin Plantinga’s view that global defeaters are possible and, once gained, are impossible to escape by reasoning. They thereby must be extinguished by other means: epistemically propitious actions, luck, or grace. I then distinguish between three types of global defeater—pure-undercutters, undercutters-because-rebutters, and undercutters-while-rebutters—and systematically consider how one can deflect such defeaters. Lastly, since I draw insights from the literature on perhaps the most (...) widely discussed global debunking argument in the literature, Plantinga’s evolutionary argument against naturalism, I end up responding to many potential problems for it. This includes the so-called conditionalization problem, as well as those raised by Bergmann (2002), Law (2012), Deem (2018), Hendricks and Anderson (2020), and Wielenberg (in Craig and Wielenberg (2021)). (shrink)