Forthcoming in Philosophical Issues, vol 18, Interdisciplinary Core Philosophy: The Metaphysics and Perception of Qualities. Alex Byrne & David Hilbert, section editors.

In this paper I critically examine the Generality Problem and argue that it does not succeed as an objection to reliabilism. Although those who urge the Generality Problem are correct in claiming that any process token can be given indefinitely many descriptions that pick out indefinitely many process types, they are mistaken in thinking that reliabilists have no principled way to distinguish between relevant and irrelevant process types.

The aim of this paper is to sketch a theory of justified belief. What I have in mind is an explanatory theory, one that explains in a general way why certain beliefs are counted as justified and others as unjustified. Unlike some traditional approaches, I do not try to prescribe standards for justification that differ from, or improve upon, our ordinary standards. I merely try to explicate the ordinary standards, which are, I believe, quite different from those of many classical, (...) e. g., ‘Cartesian’, accounts. (shrink)

The generality problem is perhaps the most notorious problem for process reliabilism. Several recent responses to the generality problem have claimed that the problem has been unfairly leveled against reliabilists. In particular, these responses have claimed that the generality problem is either (i) just as much of a problem for evidentialists, or (ii) if it is not, then a parallel solution is available to reliabilists. Along these lines, Juan Comesaña has recently proposed solution to the generality problem—well-founded reliabilism. According to (...) Comesaña, the solution to the generality problem lies in solving the basing problem, such that any solution to the basing problem will give a solution to the generality problem. Comesaña utilizes Conee and Feldman’s evidentialist account of basing (Conee and Feldman’s well-foundedness principle) in forming his version of reliabilism. In this paper I show that Comesaña’s proposed solution to the generality problem is inadequate. Well-founded reliabilism both fails to solve the generality problem and subjects reliabilism to new damning verdicts. In addition, I show that evidentialism does not face any parallel problems, so the generality problem remains a reason to prefer evidentialism to reliabilism. (shrink)

Reliabilism holds that knowledge is true belief reliably caused. Reliabilists should say something about individuating processes; critics deny that the right degree of generality can be specified without arbitrariness. It is argued that this criticism applies as well to processes mentioned in scientific explanations. The gratuitous puzzles created thereby show that the “generality problem” is illusory.

The Generality Problem is widely recognized to be a serious problem for reliabilist theories of justification. James R. Beebe's Statistical Solution is one of only a handful of attempted solutions that has garnered serious attention in the literature. In their recent response to Beebe, Julien Dutant and Erik J. Olsson successfully refute Beebe's Statistical Solution. This paper presents a New Statistical Solution that countenances Dutant and Olsson's objections, dodges the serious problems that trouble rival solutions, and retains the theoretical virtues (...) that made Beebe's solution so attractive in the first place. There indeed exists a principled, rigorous, conceptually sparse, and plausible solution to the Generality Problem: it is the New Statistical Solution. (shrink)

David Henderson and Terry Horgan argue that doxastic epistemic justification requires the transglobal reliability of the belief-forming process. Transglobal reliability is reliability across a wide range of experientially possible global environments. Focusing on perception, I argue that justification does not require transglobal reliability, for perception is non-accidentally reliable and confers justification but not always transglobally reliable. Transglobal reliability is an epistemically desirable property of belief-forming processes, but not necessary for justification.

It is common in recent epistemology to distinguish different senses, or conceptions, of epistemic justification. The proposed oppositions include the objective/subjective, internalist/externalist, regulative/nonregulative, resource-relative/resource-independent, personal/verific, and deontological/evaluative conceptions of justification. In some of these cases, writers regard both members of the contrasting pair as legitimate; in other cases only one member. In this paper I want to propose another contrasting pair of conceptions of justification, and hold that both are defensible and legitimate. The contrast will then be used to construct (...) a modified version of reliabilism, one which handles certain problem cases more naturally than my previous versions of reliabilism. (shrink)

Guided by the work of William Alston, Jonathan Adler and Michael Levin propose a solution to the generality problem for reliabilism. In some respects their proposal improves on those we have discussed. We argue that the problem remains unsolved.

According to a simple version of the reliability theory of epistemic justification, a belief is justified if and only if the process leading to that belief is reliable. The idea behind this theory is simple and attractive. There are a variety of mental or cognitive processes that result in beliefs. Some of these processes are reliable—they generally yield true beliefs—and the beliefs they produce are justified. Other processes are unreliable and the beliefs they produce are unjustified. So, for example, reliable (...) processes such as perception and memory yield justified beliefs while an unreliable process such as wishful thinking—believing something as a result of wishing that it is true—yields unjustified beliefs. (shrink)

This article is concerned with a statistical proposal due to James R. Beebe for how to solve the generality problem for process reliabilism. The proposal is highlighted by Alvin I. Goldman as an interesting candidate solution. However, Goldman raises the worry that the proposal may not always yield a determinate result. We address this worry by proving a dilemma: either the statistical approach does not yield a determinate result or it leads to trivialization, i.e. reliability collapses into truth (and anti-reliability (...) into falsehood). Various strategies for avoiding this predicament are considered, including revising the statistical rule or restricting its application to natural kinds. All amendments are seen to have serious problems of their own. We conclude that reliabilists need to look elsewhere for a convincing solution to the generality problem. (shrink)