Abstract
The paper argues that (i) the notion of epistemic reliability, as it is standardly defined within mainstream epistemology, is a multidimensional concept, and that (ii) paying attention to reliability’s multidimensional nature can significantly expand reliabilism’s purview both in the theoretical and practical domain. Reliabilist theories of knowledge and justification agree that a process is reliable just in case it leads to a ‘sufficiently high preponderance of true over false beliefs.’ Given this straightforward definition, reliability appears to be, and so far has been implicitly treated by epistemologists as, a mono-dimensional concept. Nevertheless, the terminology and formulas that statisticians and computers scientists have developed for assessing the reliability of binary classification processes reveal that for any belief-forming process whose aim is to identify the presence or the absence of some quality ι, there are at least four different interpretations of the above definition. These interpretations correspond to four separate dimensions of reliability: Precision, Negative Predictive Value (NPV), Recall and Specificity. Though epistemologists do not explicitly specify how they interpret the above definition of reliability, due to their main interest in ‘know-that’, their mono-dimensional focus seems to have so far been mainly directed at Precision alone (or, at best, to both Precision and NPV—but without distinguishing between the two). As it transpires, however, the (entirely) neglected dimensions of Recall and Specificity can guide the satisfaction of another important epistemic goal, best captured by the locution ‘know-most/all.’ The upshot is that different epistemic goals call for high levels of reliability along different dimensions (and, often, their combinations too). This observation invites upgrading reliabilism into dimensional reliabilism, according to which assessing whether a process is knowledge-conducive depends on whether it manifests high reliability along the appropriate dimension(s), given the epistemic goal at hand.