Recent epistemology has introduced a new criterion of adequacy for analyses of knowledge: such an analysis, to be adequate, must be compatible with the common view that knowledge is better than true belief. One account which is widely thought to fail this test is reliabilism, according to which, roughly, knowledge is true belief formed by reliable process. Reliabilism fails, so the argument goes, because of the "swamping problem". In brief, provided a belief is true, we do not care whether or no…
Read moreRecent epistemology has introduced a new criterion of adequacy for analyses of knowledge: such an analysis, to be adequate, must be compatible with the common view that knowledge is better than true belief. One account which is widely thought to fail this test is reliabilism, according to which, roughly, knowledge is true belief formed by reliable process. Reliabilism fails, so the argument goes, because of the "swamping problem". In brief, provided a belief is true, we do not care whether or not it was formed by a reliable process. The value of reliability is "swamped" by the value of truth: truth combined with reliability is no better than truth alone. This paper approaches these issues from the perspective of decision theory. It argues that the "swamping effect" involves a sort of information-sensitivity that is well modelled decision-theoretically. It then employs this modelling to investigate a strategy, proposed by Goldman and Olsson, for saving reliabilism from the swamp, the so-called "conditional probability solution". It concludes that the strategy is only partially successful.
